{"id":13444383,"url":"https://github.com/bismex/Awesome-person-re-identification","last_synced_at":"2025-03-20T18:32:26.088Z","repository":{"id":44896634,"uuid":"65597500","full_name":"bismex/Awesome-person-re-identification","owner":"bismex","description":"Awesome Person Re-identification","archived":false,"fork":false,"pushed_at":"2023-10-30T04:22:23.000Z","size":262,"stargazers_count":1109,"open_issues_count":1,"forks_count":194,"subscribers_count":49,"default_branch":"master","last_synced_at":"2024-05-23T07:29:16.069Z","etag":null,"topics":["awesome","awesome-list","awesome-reid","cross-modality-person","gait","identification","person-identification","person-re-identification","person-recognition","person-reid","person-reidentification","person-retrieval","re-id","reid","reidentification","vehicle-reid","vehicle-reidentification"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/bismex.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2016-08-13T03:37:18.000Z","updated_at":"2024-05-23T06:48:34.000Z","dependencies_parsed_at":"2023-01-31T20:50:11.279Z","dependency_job_id":"c71bc731-9d58-49c4-8a3e-1c867c6394b0","html_url":"https://github.com/bismex/Awesome-person-re-identification","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bismex%2FAwesome-person-re-identification","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bismex%2FAwesome-person-re-identification/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bismex%2FAwesome-person-re-identification/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bismex%2FAwesome-person-re-identification/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/bismex","download_url":"https://codeload.github.com/bismex/Awesome-person-re-identification/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":244670536,"owners_count":20491004,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["awesome","awesome-list","awesome-reid","cross-modality-person","gait","identification","person-identification","person-re-identification","person-recognition","person-reid","person-reidentification","person-retrieval","re-id","reid","reidentification","vehicle-reid","vehicle-reidentification"],"created_at":"2024-07-31T04:00:21.505Z","updated_at":"2025-03-20T18:32:25.760Z","avatar_url":"https://github.com/bismex.png","language":null,"funding_links":[],"categories":["Uncategorized","Other Lists","Computer Vision","Others"],"sub_categories":["Uncategorized","TeX Lists"],"readme":"# Awesome Person Re-identification (Person ReID) [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)\n\nThis is a repository for organizing articles related to person re-identification. Most papers are linked to the pdf address provided by \"arXiv\" or \"Openaccess\". However, some papers require an academic license to browse. For example, IEEE, springer, and elsevier journal, etc.\n\n### About Me\n- I am a proactive researcher with a solid background in computer vision and machine learning. During my PhD, I conducted profound research on person re-identification and published several papers in top-tier conferences. Additionally, I maintain a GitHub repository summarizing articles on person re-identification. After completing my PhD, I have been expanding my research into various topics, including domain generation and generative AI. Feel free to visit my **[personal homepage](https://sites.google.com/site/seokeonchoi/)**\n\n### :high_brightness: Other awesome re-identification\n- [Awesome Cross-Modality Person Re-Identification](https://github.com/bismex/Awesome-cross-modality-person-re-identification)\n- [Awesome Vehicle Re-Identification](https://github.com/bismex/Awesome-vehicle-re-identification)\n\n### :high_brightness: Other recommended related topics \n- Trajectory prediction [[github1](https://github.com/xuehaouwa/Awesome-Trajectory-Prediction)] [[github2](https://github.com/jiachenli94/Awesome-Interaction-Aware-Trajectory-Prediction)]\n- Multi-camera multi-object tracking (MCMOT) [[github1](https://github.com/luanshiyinyang/awesome-multiple-object-tracking)] [[github2](https://github.com/SherryJYC/paper-MTMC)] [[workshop:AI-city-challange](https://www.aicitychallenge.org/)] [[workshop:MMP-Tracking](https://iccv2021-mmp.github.io/)]\n\n### :high_brightness: Updated 2024-06-17\n- I have revised the page to list the most recent conferences at the top.\n- CVPR2024, WACV2024, ECCV2023 papers are updated \n\n---\n\n## Statistics\n\n| Conference  | Webpage Link | Person Re-ID | Vehicle Re-ID |\n|---           |---   |---|---|\n| [CVPR2024](#CVPR2024) | [Click](https://openaccess.thecvf.com/CVPR2024)  | 17 | 1 | \n| [WACV2024](#WACV2024) | [Click](https://openaccess.thecvf.com/WACV2024)  | 7 | 0 | \n| [ICCV2023](#ICCV2023) | [Click](https://openaccess.thecvf.com/ICCV2023)  | 13 | 0 | \n| [ACMMM2023](#ACMMM2023) | -  | - | - | \n| [CVPR2023](#CVPR2023) | [Click](https://openaccess.thecvf.com/CVPR2023)  | 11 | 0 | \n| [WACV2023](#WACV2023) | [Click](https://openaccess.thecvf.com/WACV2023) | 4 | 0 |\n| [ECCV2022](#ECCV2022) | [Click](https://eccv2022.ecva.net/program/accepted-papers/) | 10 | 2 |\n| [CVPR2022](#CVPR2022) | [Click](https://openaccess.thecvf.com/CVPR2022) | 23 | 0 |\n| [ICCV2021](#ICCV2021) | [Click](https://openaccess.thecvf.com/ICCV2021) | 24 | 2 |\n| [CVPR2021](#CVPR2021) | [Click](https://openaccess.thecvf.com/CVPR2021)  | 25 | 1 |\n| [ECCV2020](#ECCV2020) | [Click](https://eccv2020.eu/accepted-papers/)  | 25 | 3 |\n| [CVPR2020](#CVPR2020) | [Click](http://openaccess.thecvf.com/CVPR2020.py)  | 24 | 1 |\n| [ICCV2019](#ICCV2019) | [Click](http://openaccess.thecvf.com/ICCV2019.py)  | 33 | 4 |\n| [CVPR2019](#CVPR2019) | [Click](http://openaccess.thecvf.com/CVPR2019.py)  | 21 | 3 | \n| [ECCV2018](#ECCV2018) | [Click](http://openaccess.thecvf.com/ECCV2018.py)  | 15 | - | \n| [CVPR2018](#CVPR2018) | [Click](http://openaccess.thecvf.com/CVPR2018.py)  | 30 | 1 | \n| [ICCV2017](#ICCV2017) | [Click](http://openaccess.thecvf.com/ICCV2017.py)  | 14 | 1 | \n| [CVPR2017](#CVPR2017) | [Click](http://openaccess.thecvf.com/CVPR2017.py)  | 14 | - | \n\n---\n\n## Other contents\n\n- [Survey](#survey)\n- [Others](#others)\n- [Datasets](#datasets)\n- [Codes](#codes)\n\n---\n\n## CVPR2024\n\n- \u003cins\u003e***Person re-identification***\u003c/ins\u003e\n\u003e ###### 1) *\"Harnessing the Power of MLLMs for Transferable Text-to-Image Person ReID\"* [[paper](https://openaccess.thecvf.com/content/CVPR2024/papers/Tan_Harnessing_the_Power_of_MLLMs_for_Transferable_Text-to-Image_Person_ReID_CVPR_2024_paper.pdf)] [[github](https://github.com/WentaoTan/MLLM4Text-ReID)]\n\u003e ###### 2) *\"Learning Continual Compatible Representation for Re-indexing Free Lifelong Person Re-identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2024/papers/Cui_Learning_Continual_Compatible_Representation_for_Re-indexing_Free_Lifelong_Person_Re-identification_CVPR_2024_paper.pdf)] [[github](https://github.com/PKU-ICST-MIPL/C2R_CVPR2024)]\n\u003e ###### 3) *\"Attribute-Guided Pedestrian Retrieval: Bridging Person Re-ID with Internal Attribute Variability\"* [[paper](https://openaccess.thecvf.com/content/CVPR2024/papers/Huang_Attribute-Guided_Pedestrian_Retrieval_Bridging_Person_Re-ID_with_Internal_Attribute_Variability_CVPR_2024_paper.pdf)] \n\u003e ###### 4) *\"LiDAR-based Person Re-identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2024/papers/Guo_LiDAR-based_Person_Re-identification_CVPR_2024_paper.pdf)] [[github](https://github.com/GWxuan/ReID3D)]\n\u003e ###### 5) *\"A Pedestrian is Worth One Prompt: Towards Language Guidance Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2024/papers/Yang_A_Pedestrian_is_Worth_One_Prompt_Towards_Language_Guidance_Person_CVPR_2024_paper.pdf)]\n\u003e ###### 6) *\"UFineBench: Towards Text-based Person Retrieval with Ultra-fine Granularity\"* [[paper](https://openaccess.thecvf.com/content/CVPR2024/papers/Zuo_UFineBench_Towards_Text-based_Person_Retrieval_with_Ultra-fine_Granularity_CVPR_2024_paper.pdf)] [[github](https://github.com/Zplusdragon/UFineBench)]\n\u003e ###### 7) *\"Distribution-aware Knowledge Prototyping for Non-exemplar Lifelong Person Re-identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2024/papers/Xu_Distribution-aware_Knowledge_Prototyping_for_Non-exemplar_Lifelong_Person_Re-identification_CVPR_2024_paper.pdf)] [[github](https://github.com/zhoujiahuan1991/CVPR2024-DKP)]\n\u003e ###### 8) *\"Noisy-Correspondence Learning for Text-to-Image Person Re-identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2024/papers/Qin_Noisy-Correspondence_Learning_for_Text-to-Image_Person_Re-identification_CVPR_2024_paper.pdf)] [[github](https://github.com/QinYang79/RDE)]\n\u003e ###### 9) *\"Instruct-ReID: A Multi-purpose Person Re-identification Task with Instructions\"* [[paper](https://openaccess.thecvf.com/content/CVPR2024/papers/He_Instruct-ReID_A_Multi-purpose_Person_Re-identification_Task_with_Instructions_CVPR_2024_paper.pdf)] [[github](https://github.com/hwz-zju/Instruct-ReID)]\n\u003e ###### 10) *\"SEAS: ShapE-Aligned Supervision for Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2024/papers/Zhu_SEAS_ShapE-Aligned_Supervision_for_Person_Re-Identification_CVPR_2024_paper.pdf)]\n\u003e ###### 11) *\"Magic Tokens: Select Diverse Tokens for Multi-modal Object Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2024/papers/Zhang_Magic_Tokens_Select_Diverse_Tokens_for_Multi-modal_Object_Re-Identification_CVPR_2024_paper.pdf)] [[github](https://github.com/924973292/EDITOR)]\n\u003e ###### 12) *\"CA-Jaccard: Camera-aware Jaccard Distance for Person Re-identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2024/papers/Chen_CA-Jaccard_Camera-aware_Jaccard_Distance_for_Person_Re-identification_CVPR_2024_paper.pdf)] [[github](https://github.com/chen960/CA-Jaccard/)]\n\u003e ###### 13) *\"All in One Framework for Multimodal Re-identification in the Wild\"* [[paper](https://openaccess.thecvf.com/content/CVPR2024/papers/Li_All_in_One_Framework_for_Multimodal_Re-identification_in_the_Wild_CVPR_2024_paper.pdf)]\n\u003e ###### 14) *\"Shallow-Deep Collaborative Learning for Unsupervised Visible-Infrared Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2024/papers/Yang_Shallow-Deep_Collaborative_Learning_for_Unsupervised_Visible-Infrared_Person_Re-Identification_CVPR_2024_paper.pdf)] [[github](https://github.com/yangbincv/SDCL)]\n\u003e ###### 15) *\"View-decoupled Transformer for Person Re-identification under Aerial-ground Camera Network\"* [[paper](https://openaccess.thecvf.com/content/CVPR2024/papers/Zhang_View-decoupled_Transformer_for_Person_Re-identification_under_Aerial-ground_Camera_Network_CVPR_2024_paper.pdf)] [[github](https://github.com/LinlyAC/VDT-AGPReID)]\n\u003e ###### 16) *\"Implicit Discriminative Knowledge Learning for Visible-Infrared Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2024/papers/Ren_Implicit_Discriminative_Knowledge_Learning_for_Visible-Infrared_Person_Re-Identification_CVPR_2024_paper.pdf)] [[github](https://github.com/1KK077/IDKL)]\n\u003e ###### 17) *\"Activity-Biometrics: Person Identification from Daily Activities\"* [[paper](https://openaccess.thecvf.com/content/CVPR2024/papers/Azad_Activity-Biometrics_Person_Identification_from_Daily_Activities_CVPR_2024_paper.pdf)] [[github](https://github.com/sacrcv/Activity-Biometrics)]\n\n- \u003cins\u003e***Vehicle re-identification***\u003c/ins\u003e\n\u003e ###### 1) *\"Day-Night Cross-domain Vehicle Re-identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2024/papers/Li_Day-Night_Cross-domain_Vehicle_Re-identification_CVPR_2024_paper.pdf)]\n\n---\n\n## WACV2024\n\n- \u003cins\u003e***Person re-identification***\u003c/ins\u003e\n\u003e ###### 1) *\"Source-Guided Similarity Preservation for Online Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/WACV2024/papers/Rami_Source-Guided_Similarity_Preservation_for_Online_Person_Re-Identification_WACV_2024_paper.pdf)] [[github](https://github.com/ramiMMhamza/S2P)]\n\u003e ###### 2) *\"ShARc: Shape and Appearance Recognition for Person Identification In-the-wild\"* [[paper](https://openaccess.thecvf.com/content/WACV2024/papers/Zhu_ShARc_Shape_and_Appearance_Recognition_for_Person_Identification_In-the-Wild_WACV_2024_paper.pdf)]\n\u003e ###### 3) *\"Enhancing Diverse Intra-identity Representation for Visible-Infrared Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/WACV2024/papers/Kim_Enhancing_Diverse_Intra-Identity_Representation_for_Visible-Infrared_Person_Re-Identification_WACV_2024_paper.pdf)]\n\u003e ###### 4) *\"Contrastive Viewpoint-aware Shape Learning for Long-term Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/WACV2024/papers/Nguyen_Contrastive_Viewpoint-Aware_Shape_Learning_for_Long-Term_Person_Re-Identification_WACV_2024_paper.pdf)] [[github](https://github.com/jurgendn/CVSL_LReID)]\n\u003e ###### 5) *\"HashReID: Dynamic Network with Binary Codes for Efficient Person Re-identification\"* [[paper](https://openaccess.thecvf.com/content/WACV2024/papers/Nikhal_HashReID_Dynamic_Network_With_Binary_Codes_for_Efficient_Person_Re-Identification_WACV_2024_paper.pdf)]\n\u003e ###### 6) *\"Privacy-Enhancing Person Re-identification Framework – A Dual-Stage Approach\"* [[paper](https://openaccess.thecvf.com/content/WACV2024/papers/Kansal_Privacy-Enhancing_Person_Re-Identification_Framework_-_A_Dual-Stage_Approach_WACV_2024_paper.pdf)]\n\u003e ###### 7) *\"Mitigate Domain Shift by Primary-Auxiliary Objectives Association for Generalizing Person ReID\"* [[paper](https://openaccess.thecvf.com/content/WACV2024/papers/Li_Mitigate_Domain_Shift_by_Primary-Auxiliary_Objectives_Association_for_Generalizing_Person_WACV_2024_paper.pdf)]\n\n- \u003cins\u003e***Person search (detection + re-id)***\u003c/ins\u003e\n\u003e ###### 1) *\"DDAM-PS: Diligent Domain Adaptive Mixer for Person Search\"* [[paper](https://openaccess.thecvf.com/content/WACV2024/papers/Almansoori_DDAM-PS_Diligent_Domain_Adaptive_Mixer_for_Person_Search_WACV_2024_paper.pdf)] [[github](https://github.com/mustansarfiaz/DDAM-PS)]\n\n- \u003cins\u003e***Object re-identification***\u003c/ins\u003e\n\u003e ###### 1) *\"SeaTurtleID2022: A long-span dataset for reliable sea turtle re-identification\"* [[paper](https://openaccess.thecvf.com/content/WACV2024/papers/Adam_SeaTurtleID2022_A_Long-Span_Dataset_for_Reliable_Sea_Turtle_Re-Identification_WACV_2024_paper.pdf)]\n\u003e ###### 2) *\"Object Re-Identification from Point Clouds\"* [[paper](https://openaccess.thecvf.com/content/WACV2024/papers/Therien_Object_Re-Identification_From_Point_Clouds_WACV_2024_paper.pdf)] [[github](https://github.com/bentherien/point-cloud-reid)]\n\u003e ###### 3) *\"ISAR: A Benchmark for Single- and Few-Shot Object Instance Segmentation and Re-Identification\"* [[paper]([https://openaccess.thecvf.com/content/WACV2024/papers/Therien_Object_Re-Identification_From_Point_Clouds_WACV_2024_paper.pdf](https://openaccess.thecvf.com/content/WACV2024/papers/Gorlo_ISAR_A_Benchmark_for_Single-_and_Few-Shot_Object_Instance_Segmentation_WACV_2024_paper.pdf))] \n\u003e ###### 4) *\"WildlifeDatasets: An open-source toolkit for animal re-identification\"* [[paper](https://openaccess.thecvf.com/content/WACV2024/papers/Cermak_WildlifeDatasets_An_Open-Source_Toolkit_for_Animal_Re-Identification_WACV_2024_paper.pdf)] [[github](https://github.com/WildlifeDatasets/wildlife-datasets)]\n\u003e ###### 5) *\"Computer Vision on the Edge: Individual Cattle Identification in Real-time with ReadMyCow System\"* [[paper](https://openaccess.thecvf.com/content/WACV2024/papers/Smink_Computer_Vision_on_the_Edge_Individual_Cattle_Identification_in_Real-Time_WACV_2024_paper.pdf)]\n\n---\n\n## ICCV2023\n\n- \u003cins\u003e***Person re-identification***\u003c/ins\u003e\n\u003e ###### 1) *\"Identity-Seeking Self-Supervised Representation Learning for Generalizable Person Re-identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2023/papers/Dou_Identity-Seeking_Self-Supervised_Representation_Learning_for_Generalizable_Person_Re-Identification_ICCV_2023_paper.pdf)] [[github](https://github.com/dcp15/ISR_ICCV2023_Oral)]\n\u003e ###### 2) *\"Learning Clothing and Pose Invariant 3D Shape Representation for Long-Term Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2023/papers/Liu_Learning_Clothing_and_Pose_Invariant_3D_Shape_Representation_for_Long-Term_ICCV_2023_paper.pdf)] [[github](https://github.com/liufeng2915/3DInvarReID)]\n\u003e ###### 3) *\"Towards Grand Unified Representation Learning for Unsupervised Visible-Infrared Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2023/papers/Yang_Towards_Grand_Unified_Representation_Learning_for_Unsupervised_Visible-Infrared_Person_Re-Identification_ICCV_2023_paper.pdf)] [[github](https://github.com/yangbincv/GUR)]\n\u003e ###### 4) *\"A Long-Term Person Re-Identification Benchmark with Clothes Change\"* [[paper](https://openaccess.thecvf.com/content/ICCV2023/papers/Xu_DeepChange_A_Long-Term_Person_Re-Identification_Benchmark_with_Clothes_Change_ICCV_2023_paper.pdf)] [[github](https://github.com/PengBoXiangShang/deepchange)]\n\u003e ###### 5) *\"Discrepant and Multi-instance Proxies for Unsupervised Person Re-identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2023/papers/Zou_Discrepant_and_Multi-Instance_Proxies_for_Unsupervised_Person_Re-Identification_ICCV_2023_paper.pdf)]\n\u003e ###### 6) *\"Visible-Infrared Person Re-Identification via Semantic Alignment and Affinity Inference\"* [[paper](https://openaccess.thecvf.com/content/ICCV2023/papers/Fang_Visible-Infrared_Person_Re-Identification_via_Semantic_Alignment_and_Affinity_Inference_ICCV_2023_paper.pdf)] [[github](https://github.com/xiaoye-hhh/SAAI)]\n\u003e ###### 7) *\"Learning Concordant Attention via Target-aware Alignment for Visible-Infrared Person Re-identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2023/papers/Wu_Learning_Concordant_Attention_via_Target-aware_Alignment_for_Visible-Infrared_Person_Re-identification_ICCV_2023_paper.pdf)]\n\u003e ###### 8) *\"Unified Pre-training with Pseudo Texts for Text-To-Image Person Re-identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2023/papers/Shao_Unified_Pre-Training_with_Pseudo_Texts_for_Text-To-Image_Person_Re-Identification_ICCV_2023_paper.pdf)] [[github](https://github.com/ZhiyinShao-H/UniPT)]\n\u003e ###### 9) *\"Modality Unifying Network for Visible-Infrared Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2023/papers/Yu_Modality_Unifying_Network_for_Visible-Infrared_Person_Re-Identification_ICCV_2023_paper.pdf)]\n\u003e ###### 10) *\"Camera-Driven Representation Learning for Unsupervised Domain Adaptive Person Re-identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2023/papers/Lee_Camera-Driven_Representation_Learning_for_Unsupervised_Domain_Adaptive_Person_Re-identification_ICCV_2023_paper.pdf)] [[github](https://cvlab.yonsei.ac.kr/projects/CaCL/)]\n\u003e ###### 11) *\"Part-Aware Transformer for Generalizable Person Re-identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2023/papers/Ni_Part-Aware_Transformer_for_Generalizable_Person_Re-identification_ICCV_2023_paper.pdf)] [[github](https://github.com/liyuke65535/Part-Aware-Transformer)]\n\u003e ###### 12) *\"Dual Pseudo-Labels Interactive Self-Training for Semi-Supervised Visible-Infrared Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2023/papers/Shi_Dual_Pseudo-Labels_Interactive_Self-Training_for_Semi-Supervised_Visible-Infrared_Person_Re-Identification_ICCV_2023_paper.pdf)] [[github](https://github.com/XiangboYin/DPIS_SSVI-ReID)]\n\u003e ###### 13) *\"Person Re-Identification without Identification via Event Anonymization\"* [[paper](https://openaccess.thecvf.com/content/ICCV2023/papers/Ahmad_Person_Re-Identification_without_Identification_via_Event_anonymization_ICCV_2023_paper.pdf)] [[github](https://github.com/IIT-PAVIS/ReId_without_Id)]\n\n- \u003cins\u003e***Person search (detection + re-id)***\u003c/ins\u003e\n\u003e ###### 1) *\"Self-similarity Driven Scale-invariant Learning for Weakly Supervised Person Search\"* [[paper](https://openaccess.thecvf.com/content/ICCV2023/papers/Wang_Self-similarity_Driven_Scale-invariant_Learning_for_Weakly_Supervised_Person_Search_ICCV_2023_paper.pdf)] [[github](https://github.com/Wangbenzhi/SSL)]\n\n\n---\n\n## ACMMM2023\n\n- \u003cins\u003e***Person search (language or attribute)***\u003c/ins\u003e\n\u003e ###### 1) *\"Towards Unified Text-based Person Retrieval: A Large-scale Multi-Attribute and Language Search Benchmark\"* [[paper](https://zdzheng.xyz/files/MM23_Yang.pdf)] [[github](https://github.com/Shuyu-XJTU/APTM)]\n\n\n\n---\n\n## CVPR2023\n\n- \u003cins\u003e***Person re-identification***\u003c/ins\u003e\n\u003e ###### 1) *\"Diverse Embedding Expansion Network and Low-Light Cross-Modality Benchmark for Visible-Infrared Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2023/papers/Zhang_Diverse_Embedding_Expansion_Network_and_Low-Light_Cross-Modality_Benchmark_for_Visible-Infrared_CVPR_2023_paper.pdf)]\n\u003e ###### 2) *\"PHA: Patch-Wise High-Frequency Augmentation for Transformer-Based Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2023/papers/Zhang_PHA_Patch-Wise_High-Frequency_Augmentation_for_Transformer-Based_Person_Re-Identification_CVPR_2023_paper.pdf)]\n\u003e ###### 3) *\"Shape-Erased Feature Learning for Visible-Infrared Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2023/papers/Feng_Shape-Erased_Feature_Learning_for_Visible-Infrared_Person_Re-Identification_CVPR_2023_paper.pdf)]\n\u003e ###### 4) *\"TranSG: Transformer-Based Skeleton Graph Prototype Contrastive Learning With Structure-Trajectory Prompted Reconstruction for Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2023/papers/Rao_TranSG_Transformer-Based_Skeleton_Graph_Prototype_Contrastive_Learning_With_Structure-Trajectory_Prompted_CVPR_2023_paper.pdf)]\n\u003e ###### 5) *\"PartMix: Regularization Strategy To Learn Part Discovery for Visible-Infrared Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2023/papers/Kim_PartMix_Regularization_Strategy_To_Learn_Part_Discovery_for_Visible-Infrared_Person_CVPR_2023_paper.pdf)]\n\u003e ###### 6) *\"Event-Guided Person Re-Identification via Sparse-Dense Complementary Learning\"* [[paper](https://openaccess.thecvf.com/content/CVPR2023/papers/Cao_Event-Guided_Person_Re-Identification_via_Sparse-Dense_Complementary_Learning_CVPR_2023_paper.pdf)]\n\u003e ###### 7) *\"Clothing-Change Feature Augmentation for Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2023/papers/Han_Clothing-Change_Feature_Augmentation_for_Person_Re-Identification_CVPR_2023_paper.pdf)]\n\u003e ###### 8) *\"Unsupervised Visible-Infrared Person Re-Identification via Progressive Graph Matching and Alternate Learning\"* [[paper](https://openaccess.thecvf.com/content/CVPR2023/papers/Wu_Unsupervised_Visible-Infrared_Person_Re-Identification_via_Progressive_Graph_Matching_and_Alternate_CVPR_2023_paper.pdf)]\n\u003e ###### 9) *\"Towards Modality-Agnostic Person Re-Identification With Descriptive Query\"* [[paper](https://openaccess.thecvf.com/content/CVPR2023/papers/Chen_Towards_Modality-Agnostic_Person_Re-Identification_With_Descriptive_Query_CVPR_2023_paper.pdf)]\n\u003e ###### 10) *\"An In-Depth Exploration of Person Re-Identification and Gait Recognition in Cloth-Changing Conditions\"* [[paper](https://openaccess.thecvf.com/content/CVPR2023/papers/Li_An_In-Depth_Exploration_of_Person_Re-Identification_and_Gait_Recognition_in_CVPR_2023_paper.pdf)]\n\u003e ###### 11) *\"Good Is Bad: Causality Inspired Cloth-Debiasing for Cloth-Changing Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2023/papers/Yang_Good_Is_Bad_Causality_Inspired_Cloth-Debiasing_for_Cloth-Changing_Person_Re-Identification_CVPR_2023_paper.pdf)]\n\n- \u003cins\u003e***Person image synthesis / generation / reconstruction / 3D human***\u003c/ins\u003e\n\n\u003e ###### 1) *\"3DAvatarGAN: Bridging Domains for Personalized Editable Avatars\"* [[paper](https://openaccess.thecvf.com/content/CVPR2023/papers/Abdal_3DAvatarGAN_Bridging_Domains_for_Personalized_Editable_Avatars_CVPR_2023_paper.pdf)]\n\u003e ###### 2) *\"Person Image Synthesis via Denoising Diffusion Model\"* [[paper](https://openaccess.thecvf.com/content/CVPR2023/papers/Bhunia_Person_Image_Synthesis_via_Denoising_Diffusion_Model_CVPR_2023_paper.pdf)]\n\u003e ###### 3) *\"Linking Garment With Person via Semantically Associated Landmarks for Virtual Try-On\"* [[paper](https://openaccess.thecvf.com/content/CVPR2023/papers/Yan_Linking_Garment_With_Person_via_Semantically_Associated_Landmarks_for_Virtual_CVPR_2023_paper.pdf)]\n\n\n---\n\n## WACV2023\n\n- \u003cins\u003e***Person re-identification***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Body Part-Based Representation Learning for Occluded Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/WACV2023/papers/Somers_Body_Part-Based_Representation_Learning_for_Occluded_Person_Re-Identification_WACV_2023_paper.pdf)][[github](https://github.com/VlSomers/bpbreid)]\n\u003e ###### 2) *\"Graph-Based Self-Learning for Robust Person Re-identification\"* [[paper](https://openaccess.thecvf.com/content/WACV2023/papers/Xian_Graph-Based_Self-Learning_for_Robust_Person_Re-Identification_WACV_2023_paper.pdf)]\n\u003e ###### 3) *\"Feature Disentanglement Learning with Switching and Aggregation for Video-based Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/WACV2023/papers/Kim_Feature_Disentanglement_Learning_With_Switching_and_Aggregation_for_Video-Based_Person_WACV_2023_paper.pdf)]\n\u003e ###### 4) *\"Relation Preserving Triplet Mining for Stabilising the Triplet Loss in Re-identification Systems\"* [[paper](https://openaccess.thecvf.com/content/WACV2023/papers/Ghosh_Relation_Preserving_Triplet_Mining_for_Stabilising_the_Triplet_Loss_In_WACV_2023_paper.pdf)]\n\n- \u003cins\u003e***Person search (detection + re-id)***\u003c/ins\u003e\n\u003e ###### 1) *\"Gallery Filter Network for Person Search\"* [[paper](https://openaccess.thecvf.com/content/WACV2023/papers/Jaffe_Gallery_Filter_Network_for_Person_Search_WACV_2023_paper.pdf)]\n\u003e ###### 2) *\"SAT: Scale-Augmented Transformer for Person Search\"* [[paper](https://openaccess.thecvf.com/content/WACV2023/html/Fiaz_SAT_Scale-Augmented_Transformer_for_Person_Search_WACV_2023_paper.html)]\n\u003e ###### 3) *\"MEVID: Multi-view Extended Videos with Identities for Video Person Search\"* [[paper](https://openaccess.thecvf.com/content/WACV2023/papers/Davila_MEVID_Multi-View_Extended_Videos_With_Identities_for_Video_Person_Re-Identification_WACV_2023_paper.pdf)]\n\n- \u003cins\u003e***Object re-identification***\u003c/ins\u003e\n\u003e ###### 1) *\"Bent \u0026 Broken Bicycles: Leveraging synthetic data for damaged object re-identification\"* [[paper](https://openaccess.thecvf.com/content/WACV2023/papers/Piano_Bent__Broken_Bicycles_Leveraging_Synthetic_Data_for_Damaged_Object_WACV_2023_paper.pdf)]\n\n\n\n---\n\n## ECCV2022\n\n- \u003cins\u003e***Person re-identification***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Optimal Transport for Label-Efficient Visible-Infrared Person Re-Identification\"* [[paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136840091.pdf)]\n\u003e ###### 2) *\"PASS: Part-Aware Self-Supervised Pre-Training for Person Re-Identification\"* [[paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136740192.pdf)]\n\u003e ###### 3) *\"Adaptive Cross-Domain Learning for Generalizable Person Re-Identification\"* [[paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136740209.pdf)]\n\u003e ###### 4) *\"Dynamically Transformed Instance Normalization Network for Generalizable Person Re-Identification\"* [[paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136740279.pdf)]\n\u003e ###### 5) *\"Mimic Embedding via Adaptive Aggregation: Learning Generalizable Person Re-identification\"* [[paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136740362.pdf)]\n\u003e ###### 6) *\"Counterfactual Intervention Feature Transfer for Visible-Infrared Person Re-identification\"* [[paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136860371.pdf)]\n\u003e ###### 7) *\"Modality Synergy Complement Learning with Cascaded Aggregation for Visible-Infrared Person Re-Identification\"* [[paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136740450.pdf)]\n\u003e ###### 8) *\"Cross-Modality Transformer for Visible-Infrared Person Re-Identification\"* [[paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136740467.pdf)]\n\u003e ###### 9) *\"CAViT: Contextual Alignment Vision Transformer for Video Object Re-identification\"* [[paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136740535.pdf)]\n\u003e ###### 10) *\"Reliability-Aware Prediction via Uncertainty Learning for Person Image Retrieval\"* [[paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136740572.pdf)]\n\n- \u003cins\u003e***Vehicle re-identification***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Unstructured Feature Decoupling for Vehicle Re-Identification\"* [[paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136740328.pdf)]\n\u003e ###### 2) *\"RVSL: Robust Vehicle Similarity Learning in Real Hazy Scenes Based on Semi-supervised Learning\"* [[paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136740415.pdf)]\n\n- \u003cins\u003e***Person search (detection + re-id)***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Domain Adaptive Person Search\"* [[paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136740295.pdf)]\n\u003e ###### 2) *\"OIMNet++: Prototypical Normalization and Localization-aware Learning for Person Search\"* [[paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136700615.pdf)]\n\n- \u003cins\u003e***Person search (language or attribute)***\u003c/ins\u003e\n\n\u003e ###### 1) *\"A Simple and Robust Correlation Filtering method for text-based person search\"* [[paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136950719.pdf)]\n\n- \u003cins\u003e***Object re-identification***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Negative Samples are at Large: Leveraging Hard-distance Elastic Loss for Re-identification\"* [[paper](https://arxiv.org/pdf/2207.09884.pdf)]\n\n- \u003cins\u003e***Person image synthesis / generation / reconstruction / 3D human***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Cross Attention Based Style Distribution for Controllable Person Image Synthesis\"* [[paper](https://arxiv.org/pdf/2208.00712.pdf)]\n\u003e ###### 2) *\"FLEX: Extrinsic Parameters-free Multi-view 3D Human Motion Reconstruction\"* [[paper](https://arxiv.org/pdf/2105.01937.pdf)]\n\u003e ###### 3) *\"DiffuStereo: High Quality Human Reconstruction via Diffusion-based Stereo Using Sparse Cameras\"* [[paper](https://arxiv.org/pdf/2207.08000.pdf)]\n\u003e ###### 4) *\"UNIF: United Neural Implicit Functions for Clothed Human Reconstruction and Animation\"* [[paper](https://arxiv.org/pdf/2207.09835.pdf)]\n\u003e ###### 5) *\"3D Clothed Human Reconstruction in the Wild\"* [[paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136620177.pdf)]\n\u003e ###### 6) *\"Compositional Human-Scene Interaction Synthesis with Semantic Control\"* [[paper](https://arxiv.org/pdf/2207.12824.pdf)]\n\u003e ###### 7) *\"IntegratedPIFu: Integrated Pixel Aligned Implicit Function for Single-view Human Reconstruction\"* [[paper](https://arxiv.org/pdf/2211.07955.pdf)]\n\u003e ###### 8) *\"PoseGPT: Quantization-based 3D Human Motion Generation and Forecasting\"* [[paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136660409.pdf)]\n\u003e ###### 9) *\"Implicit Neural Representations for Variable Length Human Motion Generation\"* [[paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136770359.pdf)]\n\u003e ###### 10) *\"3D-Aware Semantic-Guided Generative Model for Human Synthesis\"* [[paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136750337.pdf)]\n\n\n\n---\n\n## CVPR2022\n\n- \u003cins\u003e***Person re-identification***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Cloning Outfits From Real-World Images to 3D Characters for Generalizable Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Wang_Cloning_Outfits_From_Real-World_Images_to_3D_Characters_for_Generalizable_CVPR_2022_paper.pdf)]\n\u003e ###### 2) *\"Unleashing Potential of Unsupervised Pre-Training With Intra-Identity Regularization for Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Yang_Unleashing_Potential_of_Unsupervised_Pre-Training_With_Intra-Identity_Regularization_for_Person_CVPR_2022_paper.pdf)]\n\u003e ###### 3) *\"Clothes-Changing Person Re-Identification With RGB Modality Only\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Gu_Clothes-Changing_Person_Re-Identification_With_RGB_Modality_Only_CVPR_2022_paper.pdf)]\n\u003e ###### 4) *\"Part-Based Pseudo Label Refinement for Unsupervised Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Cho_Part-Based_Pseudo_Label_Refinement_for_Unsupervised_Person_Re-Identification_CVPR_2022_paper.pdf)]\n\u003e ###### 5) *\"Learning With Twin Noisy Labels for Visible-Infrared Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Yang_Learning_With_Twin_Noisy_Labels_for_Visible-Infrared_Person_Re-Identification_CVPR_2022_paper.pdf)]\n\u003e ###### 6) *\"FMCNet: Feature-Level Modality Compensation for Visible-Infrared Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Zhang_FMCNet_Feature-Level_Modality_Compensation_for_Visible-Infrared_Person_Re-Identification_CVPR_2022_paper.pdf)]\n\u003e ###### 7) *\"Lifelong Unsupervised Domain Adaptive Person Re-Identification With Coordinated Anti-Forgetting and Adaptation\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Huang_Lifelong_Unsupervised_Domain_Adaptive_Person_Re-Identification_With_Coordinated_Anti-Forgetting_and_CVPR_2022_paper.pdf)]\n\u003e ###### 8) *\"Large-Scale Pre-Training for Person Re-Identification With Noisy Labels\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Fu_Large-Scale_Pre-Training_for_Person_Re-Identification_With_Noisy_Labels_CVPR_2022_paper.pdf)]\n\u003e ###### 9) *\"Feature Erasing and Diffusion Network for Occluded Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Wang_Feature_Erasing_and_Diffusion_Network_for_Occluded_Person_Re-Identification_CVPR_2022_paper.pdf)]\n\u003e ###### 10) *\"Learning Memory-Augmented Unidirectional Metrics for Cross-Modality Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Liu_Learning_Memory-Augmented_Unidirectional_Metrics_for_Cross-Modality_Person_Re-Identification_CVPR_2022_paper.pdf)]\n\u003e ###### 11) *\"Graph Sampling Based Deep Metric Learning for Generalizable Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Liao_Graph_Sampling_Based_Deep_Metric_Learning_for_Generalizable_Person_Re-Identification_CVPR_2022_paper.pdf)]\n\u003e ###### 12) *\"Augmented Geometric Distillation for Data-Free Incremental Person ReID\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Lu_Augmented_Geometric_Distillation_for_Data-Free_Incremental_Person_ReID_CVPR_2022_paper.pdf)]\n\u003e ###### 13) *\"Salient-to-Broad Transition for Video Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Bai_Salient-to-Broad_Transition_for_Video_Person_Re-Identification_CVPR_2022_paper.pdf)]\n\u003e ###### 14) *\"NFormer: Robust Person Re-Identification With Neighbor Transformer\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Wang_NFormer_Robust_Person_Re-Identification_With_Neighbor_Transformer_CVPR_2022_paper.pdf)]\n\u003e ###### 15) *\"Implicit Sample Extension for Unsupervised Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Zhang_Implicit_Sample_Extension_for_Unsupervised_Person_Re-Identification_CVPR_2022_paper.pdf)]\n\u003e ###### 16) *\"Cloth-Changing Person Re-Identification From a Single Image With Gait Prediction and Regularization\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Jin_Cloth-Changing_Person_Re-Identification_From_a_Single_Image_With_Gait_Prediction_CVPR_2022_paper.pdf)]\n\u003e ###### 17) *\"Learning Modal-Invariant and Temporal-Memory for Video-Based Visible-Infrared Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Lin_Learning_Modal-Invariant_and_Temporal-Memory_for_Video-Based_Visible-Infrared_Person_Re-Identification_CVPR_2022_paper.pdf)]\n\u003e ###### 18) *\"Meta Distribution Alignment for Generalizable Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Ni_Meta_Distribution_Alignment_for_Generalizable_Person_Re-Identification_CVPR_2022_paper.pdf)]\n\u003e ###### 19) *\"Camera-Conditioned Stable Feature Generation for Isolated Camera Supervised Person Re-IDentification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Wu_Camera-Conditioned_Stable_Feature_Generation_for_Isolated_Camera_Supervised_Person_Re-IDentification_CVPR_2022_paper.pdf)]\n\u003e ###### 20) *\"AutoLoss-GMS: Searching Generalized Margin-Based Softmax Loss Function for Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Gu_AutoLoss-GMS_Searching_Generalized_Margin-Based_Softmax_Loss_Function_for_Person_Re-Identification_CVPR_2022_paper.pdf)]\n\u003e ###### 21) *\"Temporal Complementarity-Guided Reinforcement Learning for Image-to-Video Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Wu_Temporal_Complementarity-Guided_Reinforcement_Learning_for_Image-to-Video_Person_Re-Identification_CVPR_2022_paper.pdf)]\n\u003e ###### 22) *\"Modeling 3D Layout For Group Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Zhang_Modeling_3D_Layout_for_Group_Re-Identification_CVPR_2022_paper.pdf)]\n\u003e ###### 23) *\"Connecting the Complementary-view Videos: Joint Camera Identification and Subject Association\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Han_Connecting_the_Complementary-View_Videos_Joint_Camera_Identification_and_Subject_Association_CVPR_2022_paper.pdf)]\n\n- \u003cins\u003e***Person search (detection + re-id)***\u003c/ins\u003e\n\n\u003e ###### 1) *\"PSTR: End-to-End One-Step Person Search With Transformers\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Cao_PSTR_End-to-End_One-Step_Person_Search_With_Transformers_CVPR_2022_paper.pdf)]\n\u003e ###### 2) *\"PoseTrack21: A Dataset for Person Search, Multi-Object Tracking and Multi-Person Pose Tracking\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Doring_PoseTrack21_A_Dataset_for_Person_Search_Multi-Object_Tracking_and_Multi-Person_CVPR_2022_paper.pdf)]\n\u003e ###### 3) *\"Cascade Transformers for End-to-End Person Search\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Yu_Cascade_Transformers_for_End-to-End_Person_Search_CVPR_2022_paper.pdf)]\n\u003e ###### 4) *\"Id-Free Person Similarity Learning\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Shuai_Id-Free_Person_Similarity_Learning_CVPR_2022_paper.pdf)]\n\n- \u003cins\u003e***Object re-identification***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Dual Cross-Attention Learning for Fine-Grained Visual Categorization and Object Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Zhu_Dual_Cross-Attention_Learning_for_Fine-Grained_Visual_Categorization_and_Object_Re-Identification_CVPR_2022_paper.pdf)]\n\u003e ###### 2) *\"Neural Face Identification in a 2D Wireframe Projection of a Manifold Object\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Wang_Neural_Face_Identification_in_a_2D_Wireframe_Projection_of_a_CVPR_2022_paper.pdf)]\n\u003e ###### 3) *\"AirObject: A Temporally Evolving Graph Embedding for Object Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Keetha_AirObject_A_Temporally_Evolving_Graph_Embedding_for_Object_Identification_CVPR_2022_paper.pdf)]\n\n- \u003cins\u003e***Person image synthesis / generation***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Exploring Dual-Task Correlation for Pose Guided Person Image Generation\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Zhang_Exploring_Dual-Task_Correlation_for_Pose_Guided_Person_Image_Generation_CVPR_2022_paper.pdf)]\n\u003e ###### 2) *\"Neural Texture Extraction and Distribution for Controllable Person Image Synthesis\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Ren_Neural_Texture_Extraction_and_Distribution_for_Controllable_Person_Image_Synthesis_CVPR_2022_paper.pdf)]\n\u003e ###### 3) *\"Self-Supervised Correlation Mining Network for Person Image Generation\"* [[paper](https://openaccess.thecvf.com/content/CVPR2022/papers/Wang_Self-Supervised_Correlation_Mining_Network_for_Person_Image_Generation_CVPR_2022_paper.pdf)]\n\n\n\n---\n\n## ICCV2021\n\n- \u003cins\u003e***Person re-identification***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Cross-Modality Person Re-Identification via Modality Confusion and Center Aggregation\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Hao_Cross-Modality_Person_Re-Identification_via_Modality_Confusion_and_Center_Aggregation_ICCV_2021_paper.pdf)]\n\u003e ###### 2) *\"Clothing Status Awareness for Long-Term Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Huang_Clothing_Status_Awareness_for_Long-Term_Person_Re-Identification_ICCV_2021_paper.pdf)]\n\u003e ###### 3) *\"Dense Interaction Learning for Video-Based Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/He_Dense_Interaction_Learning_for_Video-Based_Person_Re-Identification_ICCV_2021_paper.pdf)]\n\u003e ###### 4) *\"Explainable Person Re-Identification With Attribute-Guided Metric Distillation\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Chen_Explainable_Person_Re-Identification_With_Attribute-Guided_Metric_Distillation_ICCV_2021_paper.pdf)] [[github](http://xiaodongchen.cn/AMD.github.io/)]\n\u003e ###### 5) *\"Online Pseudo Label Generation by Hierarchical Cluster Dynamics for Adaptive Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Zheng_Online_Pseudo_Label_Generation_by_Hierarchical_Cluster_Dynamics_for_Adaptive_ICCV_2021_paper.pdf)]\n\u003e ###### 6) *\"Multi-Expert Adversarial Attack Detection in Person Re-Identification Using Context Inconsistency\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Wang_Multi-Expert_Adversarial_Attack_Detection_in_Person_Re-Identification_Using_Context_Inconsistency_ICCV_2021_paper.pdf)]\n\u003e ###### 7) *\"Pyramid Spatial-Temporal Aggregation for Video-Based Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Wang_Pyramid_Spatial-Temporal_Aggregation_for_Video-Based_Person_Re-Identification_ICCV_2021_paper.pdf)] [[github](https://github.com/WangYQ9/VideoReID_PSTA)]\n\u003e ###### 8) *\"ICE: Inter-Instance Contrastive Encoding for Unsupervised Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Chen_ICE_Inter-Instance_Contrastive_Encoding_for_Unsupervised_Person_Re-Identification_ICCV_2021_paper.pdf)] [[github](https://github.com/chenhao2345/ICE)]\n\u003e ###### 9) *\"BV-Person: A Large-Scale Dataset for Bird-View Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Yan_BV-Person_A_Large-Scale_Dataset_for_Bird-View_Person_Re-Identification_ICCV_2021_paper.pdf)] [[github](https://github.com/daidaidouer/BVPerson)]\n\u003e ###### 10) *\"Learning To Know Where To See: A Visibility-Aware Approach for Occluded Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Yang_Learning_To_Know_Where_To_See_A_Visibility-Aware_Approach_for_ICCV_2021_paper.pdf)]\n\u003e ###### 11) *\"CM-NAS: Cross-Modality Neural Architecture Search for Visible-Infrared Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Fu_CM-NAS_Cross-Modality_Neural_Architecture_Search_for_Visible-Infrared_Person_Re-Identification_ICCV_2021_paper.pdf)] [[github](https://github.com/JDAI-CV/CM-NAS)]\n\u003e ###### 12) *\"Meta Pairwise Relationship Distillation for Unsupervised Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Ji_Meta_Pairwise_Relationship_Distillation_for_Unsupervised_Person_Re-Identification_ICCV_2021_paper.pdf)]\n\u003e ###### 13) *\"Syncretic Modality Collaborative Learning for Visible Infrared Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Wei_Syncretic_Modality_Collaborative_Learning_for_Visible_Infrared_Person_Re-Identification_ICCV_2021_paper.pdf)]\n\u003e ###### 14) *\"Towards Discriminative Representation Learning for Unsupervised Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Isobe_Towards_Discriminative_Representation_Learning_for_Unsupervised_Person_Re-Identification_ICCV_2021_paper.pdf)]\n\u003e ###### 15) *\"Video-Based Person Re-Identification With Spatial and Temporal Memory Networks\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Eom_Video-Based_Person_Re-Identification_With_Spatial_and_Temporal_Memory_Networks_ICCV_2021_paper.pdf)] [[github](https://cvlab.yonsei.ac.kr/projects/STMN/)]\n\u003e ###### 16) *\"Learning by Aligning: Visible-Infrared Person Re-Identification Using Cross-Modal Correspondences\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Park_Learning_by_Aligning_Visible-Infrared_Person_Re-Identification_Using_Cross-Modal_Correspondences_ICCV_2021_paper.pdf)] [[github](https://cvlab.yonsei.ac.kr/projects/LbA/)]\n\u003e ###### 17) *\"Spatio-Temporal Representation Factorization for Video-Based Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Aich_Spatio-Temporal_Representation_Factorization_for_Video-Based_Person_Re-Identification_ICCV_2021_paper.pdf)]\n\u003e ###### 18) *\"IDM: An Intermediate Domain Module for Domain Adaptive Person Re-ID\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Dai_IDM_An_Intermediate_Domain_Module_for_Domain_Adaptive_Person_Re-ID_ICCV_2021_paper.pdf)] [[github](https://github.com/SikaStar/IDM)]\n\u003e ###### 19) *\"Weakly Supervised Text-Based Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Zhao_Weakly_Supervised_Text-Based_Person_Re-Identification_ICCV_2021_paper.pdf)] [[github](https://github.com/X-BrainLab/WS_Text-ReID)]\n\u003e ###### 20) *\"Occlude Them All: Occlusion-Aware Attention Network for Occluded Person Re-ID\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Chen_Occlude_Them_All_Occlusion-Aware_Attention_Network_for_Occluded_Person_Re-ID_ICCV_2021_paper.pdf)]\n\u003e ###### 21) *\"Occluded Person Re-Identification With Single-Scale Global Representations\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Yan_Occluded_Person_Re-Identification_With_Single-Scale_Global_Representations_ICCV_2021_paper.pdf)] [[github](https://github.com/daidaidouer/OP-ReID)]\n\u003e ###### 22) *\"Learning Instance-Level Spatial-Temporal Patterns for Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Ren_Learning_Instance-Level_Spatial-Temporal_Patterns_for_Person_Re-Identification_ICCV_2021_paper.pdf)] [[github](https://github.com/RenMin1991/cleaned-DukeMTMC-reID/)]\n\u003e ###### 23) *\"TransReID: Transformer-Based Object Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/He_TransReID_Transformer-Based_Object_Re-Identification_ICCV_2021_paper.pdf)] [[github](https://github.com/heshuting555/TransReID)]\n\u003e ###### 24) *\"Attack-Guided Perceptual Data Generation for Real-World Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Huang_Attack-Guided_Perceptual_Data_Generation_for_Real-World_Re-Identification_ICCV_2021_paper.pdf)]\n\n- \u003cins\u003e***Vehicle re-identification***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Self-Supervised Geometric Features Discovery via Interpretable Attention for Vehicle Re-Identification and Beyond\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Li_Self-Supervised_Geometric_Features_Discovery_via_Interpretable_Attention_for_Vehicle_Re-Identification_ICCV_2021_paper.pdf)]\n\u003e ###### 2) *\"Heterogeneous Relational Complement for Vehicle Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Zhao_Heterogeneous_Relational_Complement_for_Vehicle_Re-Identification_ICCV_2021_paper.pdf)]\n \n- \u003cins\u003e***Person search (detection + re-id)***\u003c/ins\u003e\n\n\u003e ###### 1) *\"End-to-End Trainable Trident Person Search Network Using Adaptive Gradient Propagation\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Han_End-to-End_Trainable_Trident_Person_Search_Network_Using_Adaptive_Gradient_Propagation_ICCV_2021_paper.pdf)]\n\u003e ###### 2) *\"Weakly Supervised Person Search With Region Siamese Networks\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Han_Weakly_Supervised_Person_Search_With_Region_Siamese_Networks_ICCV_2021_paper.pdf)]\n\n- \u003cins\u003e***Person search (language or attribute)***\u003c/ins\u003e\n\n\u003e ###### 1) *\"LapsCore: Language-Guided Person Search via Color Reasoning\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Wu_LapsCore_Language-Guided_Person_Search_via_Color_Reasoning_ICCV_2021_paper.pdf)]\n\u003e ###### 2) *\"ASMR: Learning Attribute-Based Person Search With Adaptive Semantic Margin Regularizer\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Jeong_ASMR_Learning_Attribute-Based_Person_Search_With_Adaptive_Semantic_Margin_Regularizer_ICCV_2021_paper.pdf)] [[github](http://cvlab.postech.ac.kr/research/ASMR/)]\n\n- \u003cins\u003e***Object re-identification***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Rao_Counterfactual_Attention_Learning_for_Fine-Grained_Visual_Categorization_and_Re-Identification_ICCV_2021_paper.pdf)] [[github](https://github.com/raoyongming/CAL)]\n\n- \u003cins\u003e***Person image synthesis / generation***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Dressing in Order: Recurrent Person Image Generation for Pose Transfer, Virtual Try-On and Outfit Editing\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Cui_Dressing_in_Order_Recurrent_Person_Image_Generation_for_Pose_Transfer_ICCV_2021_paper.pdf)] [[github](https://github.com/cuiaiyu/dressing-in-order)]\n\u003e ###### 2) *\"Structure-Transformed Texture-Enhanced Network for Person Image Synthesis\"* [[paper](https://openaccess.thecvf.com/content/ICCV2021/papers/Xu_Structure-Transformed_Texture-Enhanced_Network_for_Person_Image_Synthesis_ICCV_2021_paper.pdf)]\n\n\n\n\n---\n\n## CVPR2021\n\n- \u003cins\u003e***Person re-identification***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Meta Batch-Instance Normalization for Generalizable Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Choi_Meta_Batch-Instance_Normalization_for_Generalizable_Person_Re-Identification_CVPR_2021_paper.pdf)][[github](https://github.com/bismex/MetaBIN)]\n\u003e ###### 2) *\"Intra-Inter Camera Similarity for Unsupervised Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Xuan_Intra-Inter_Camera_Similarity_for_Unsupervised_Person_Re-Identification_CVPR_2021_paper.pdf)][[github](https://github.com/SY-Xuan/IICS)]\n\u003e ###### 3) *\"Joint Noise-Tolerant Learning and Meta Camera Shift Adaptation for Unsupervised Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Yang_Joint_Noise-Tolerant_Learning_and_Meta_Camera_Shift_Adaptation_for_Unsupervised_CVPR_2021_paper.pdf)][[github](https://github.com/FlyingRoastDuck/MetaCam_DSCE)]\n\u003e ###### 4) *\"Watching You: Global-guided Reciprocal Learning for Video-based Person Re-identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Liu_Watching_You_Global-Guided_Reciprocal_Learning_for_Video-Based_Person_Re-Identification_CVPR_2021_paper.pdf)]\n\u003e ###### 5) *\"Lifelong Person Re-Identification via Adaptive Knowledge Accumulation\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Pu_Lifelong_Person_Re-Identification_via_Adaptive_Knowledge_Accumulation_CVPR_2021_paper.pdf)][[github](https://github.com/TPCD/LifelongReID)]\n\u003e ###### 6) *\"Group-aware Label Transfer for Domain Adaptive Person Re-identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Zheng_Group-aware_Label_Transfer_for_Domain_Adaptive_Person_Re-identification_CVPR_2021_paper.pdf)][[github](https://github.com/zkcys001/UDAStrongBaseline)]\n\u003e ###### 6) *\"Combined Depth Space based Architecture Search For Person Re-identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Li_Combined_Depth_Space_Based_Architecture_Search_for_Person_Re-Identification_CVPR_2021_paper.pdf)]\n\u003e ###### 7) *\"Neural Feature Search for RGB-Infrared Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Chen_Neural_Feature_Search_for_RGB-Infrared_Person_Re-Identification_CVPR_2021_paper.pdf)]\n\u003e ###### 8) *\"Learning to Generalize Unseen Domains via Memory-based Multi-Source Meta-Learning for Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Zhao_Learning_to_Generalize_Unseen_Domains_via_Memory-based_Multi-Source_Meta-Learning_for_CVPR_2021_paper.pdf)][[github](https://github.com/HeliosZhao/M3L)]\n\u003e ###### 9) *\"Unsupervised Multi-Source Domain Adaptation for Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Bai_Unsupervised_Multi-Source_Domain_Adaptation_for_Person_Re-Identification_CVPR_2021_paper.pdf)] [[github](https://github.com/Neverland610/MSUDA_REID/)]\n\u003e ###### 10) *\"Coarse-To-Fine Person Re-Identification With Auxiliary-Domain Classification and Second-Order Information Bottleneck\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Zhang_Coarse-To-Fine_Person_Re-Identification_With_Auxiliary-Domain_Classification_and_Second-Order_Information_Bottleneck_CVPR_2021_paper.pdf)]\n\u003e ###### 11) *\"Farewell to Mutual Information: Variational Distillation for Cross-Modal Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Tian_Farewell_to_Mutual_Information_Variational_Distillation_for_Cross-Modal_Person_Re-Identification_CVPR_2021_paper.pdf)]\n\u003e ###### 12) *\"Joint Generative and Contrastive Learning for Unsupervised Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Chen_Joint_Generative_and_Contrastive_Learning_for_Unsupervised_Person_Re-Identification_CVPR_2021_paper.pdf)]\n\u003e ###### 13) *\"BiCnet-TKS: Learning Efficient Spatial-Temporal Representation for Video Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Hou_BiCnet-TKS_Learning_Efficient_Spatial-Temporal_Representation_for_Video_Person_Re-Identification_CVPR_2021_paper.pdf)]\n\u003e ###### 14) *\"Person30K: A Dual-Meta Generalization Network for Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Bai_Person30K_A_Dual-Meta_Generalization_Network_for_Person_Re-Identification_CVPR_2021_paper.pdf)]\n\u003e ###### 15) *\"Diverse Part Discovery: Occluded Person Re-Identification With Part-Aware Transformer\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Li_Diverse_Part_Discovery_Occluded_Person_Re-Identification_With_Part-Aware_Transformer_CVPR_2021_paper.pdf)]\n\u003e ###### 16) *\"Discover Cross-Modality Nuances for Visible-Infrared Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Wu_Discover_Cross-Modality_Nuances_for_Visible-Infrared_Person_Re-Identification_CVPR_2021_paper.pdf)]\n\u003e ###### 17) *\"Spatial-Temporal Correlation and Topology Learning for Person Re-Identification in Videos\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Liu_Spatial-Temporal_Correlation_and_Topology_Learning_for_Person_Re-Identification_in_Videos_CVPR_2021_paper.pdf)]\n\u003e ###### 18) *\"Learning 3D Shape Feature for Texture-Insensitive Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Chen_Learning_3D_Shape_Feature_for_Texture-Insensitive_Person_Re-Identification_CVPR_2021_paper.pdf)]\n\u003e ###### 19) *\"Partial Person Re-Identification With Part-Part Correspondence Learning\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/He_Partial_Person_Re-Identification_With_Part-Part_Correspondence_Learning_CVPR_2021_paper.pdf)]\n\u003e ###### 20) *\"Fine-Grained Shape-Appearance Mutual Learning for Cloth-Changing Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Hong_Fine-Grained_Shape-Appearance_Mutual_Learning_for_Cloth-Changing_Person_Re-Identification_CVPR_2021_paper.pdf)]\n\u003e ###### 21) *\"UnrealPerson: An Adaptive Pipeline Towards Costless Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Zhang_UnrealPerson_An_Adaptive_Pipeline_Towards_Costless_Person_Re-Identification_CVPR_2021_paper.pdf)]\n\u003e ###### 22) *\"Person Re-Identification Using Heterogeneous Local Graph Attention Networks\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Zhang_Person_Re-Identification_Using_Heterogeneous_Local_Graph_Attention_Networks_CVPR_2021_paper.pdf)]\n\u003e ###### 23) *\"Wide-Baseline Multi-Camera Calibration Using Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Xu_Wide-Baseline_Multi-Camera_Calibration_Using_Person_Re-Identification_CVPR_2021_paper.pdf)]\n\u003e ###### 24) *\"Unsupervised Pre-Training for Person Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Xu_Wide-Baseline_Multi-Camera_Calibration_Using_Person_Re-Identification_CVPR_2021_paper.pdf)]\n\u003e ###### 25) *\"Generalizable Person Re-Identification With Relevance-Aware Mixture of Experts\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Dai_Generalizable_Person_Re-Identification_With_Relevance-Aware_Mixture_of_Experts_CVPR_2021_paper.pdf)]\n\n\n- \u003cins\u003e***Vehicle re-identification***\u003c/ins\u003e\n\n\u003e ###### 1) *\"PhD Learning: Learning With Pompeiu-Hausdorff Distances for Video-Based Vehicle Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Zhao_PhD_Learning_Learning_With_Pompeiu-Hausdorff_Distances_for_Video-Based_Vehicle_Re-Identification_CVPR_2021_paper.pdf)]\n\n\n- \u003cins\u003e***Person search (detection + re-id)***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Anchor-Free Person Search\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Yan_Anchor-Free_Person_Search_CVPR_2021_paper.pdf)]\n\u003e ###### 2) *\"Prototype-Guided Saliency Feature Learning for Person Search\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Kim_Prototype-Guided_Saliency_Feature_Learning_for_Person_Search_CVPR_2021_paper.pdf)]\n\n- \u003cins\u003e***Object re-identification***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Refining Pseudo Labels With Clustering Consensus Over Generations for Unsupervised Object Re-Identification\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Zhang_Refining_Pseudo_Labels_With_Clustering_Consensus_Over_Generations_for_Unsupervised_CVPR_2021_paper.pdf)]\n\n- \u003cins\u003e***Person image synthesis / generation***\u003c/ins\u003e\n\n\u003e ###### 1) *\"PISE: Person Image Synthesis and Editing With Decoupled GAN\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Zhang_PISE_Person_Image_Synthesis_and_Editing_With_Decoupled_GAN_CVPR_2021_paper.pdf)]\n\u003e ###### 2) *\"Learning Semantic Person Image Generation by Region-Adaptive Normalization\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Lv_Learning_Semantic_Person_Image_Generation_by_Region-Adaptive_Normalization_CVPR_2021_paper.pdf)]\n\u003e ###### 3) *\"MUST-GAN: Multi-Level Statistics Transfer for Self-Driven Person Image Generation\"* [[paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Ma_MUST-GAN_Multi-Level_Statistics_Transfer_for_Self-Driven_Person_Image_Generation_CVPR_2021_paper.pdf)]\n\n\n\n---\n\n## ECCV2020\n\n- \u003cins\u003e***Person re-identification***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Joint Disentangling and Adaptation for Cross-Domain Person Re-Identification\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123470086.pdf)]\n\u003e ###### 2) *\"Appearance-Preserving 3D Convolution for Video-based Person Re-identification\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123470222.pdf)]\n\u003e ###### 3) *\"Identity-Guided Human Semantic Parsing for Person Re-Identification\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123480358.pdf)]\n\u003e ###### 4) *\"Do Not Disturb Me: Person Re-identification Under the Interference of Other Pedestrians\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510647.pdf)]\n\u003e ###### 5) *\"Multiple Expert Brainstorming for Domain Adaptive Person Re-identification\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520579.pdf)]\n\u003e ###### 6) *\"Global Distance-distributions Separation for Unsupervised Person Re-identification\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520715.pdf)]\n\u003e ###### 7) *\"Faster Person Re-Identification\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123530273.pdf)]\n\u003e ###### 8) *\"Deep Credible Metric Learning for Unsupervised Domain Adaptation Person Re-identification\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123530630.pdf)]\n\u003e ###### 9) *\"Temporal Coherence or Temporal Motion: Which is More Critical for Video-based Person Re-identification?\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123530647.pdf)]\n\u003e ###### 10) *\"Interpretable and Generalizable Person Re-identification with Query-adaptive Convolution and Temporal Lifting\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123560443.pdf)]\n\u003e ###### 11) *\"Unsupervised Domain Adaptation with Noise Resistible Mutual-Training for Person Re-identification\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123560511.pdf)]\n\u003e ###### 12) *\"Rethinking the Distribution Gap of Person Re-identification with Camera-based Batch Normalization\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123570137.pdf)]\n\u003e ###### 13) *\"Generalizing Person Re-Identification by Camera-Aware Invariance Learning and Cross-Domain Mixup\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123600222.pdf)]\n\u003e ###### 14) *\"Dynamic Dual-Attentive Aggregation Learning for Visible-Infrared Person Re-Identification\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123620222.pdf)]\n\u003e ###### 15) *\"Joint Visual and Temporal Consistency for Unsupervised Domain Adaptive Person Re-Identification\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123690477.pdf)]\n\u003e ###### 16) *\"Temporal Complementary Learning for Video Person Re-Identification\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123700392.pdf)]\n\u003e ###### 17) *\"Prediction and Recovery for Adaptive Low-Resolution Person Re-Identification\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123710188.pdf)]\n\u003e ###### 18) *\"An Attention-driven Two-stage Clustering Method for Unsupervised Person Re-Identification\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123730018.pdf)]\n\u003e ###### 19) *\"Guided Saliency Feature Learning for Person Re-identification in Crowded Scenes\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123730358.pdf)]\n\u003e ###### 20) *\"Robust Re-Identification by Multiple Views Knowledge Distillation\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123550103.pdf)]\n\u003e ###### 21) *\"Character Grounding and Re-Identification in Story of Videos and Text Descriptions\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500528.pdf)]\n\u003e ###### 22) *\"ReAD: Reciprocal Attention Discriminator for Image-to-Video Re-Identification\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123590324.pdf)]\n\u003e ###### 23) *\"Exploiting Temporal Coherence for Self-Supervised One-shot Video Re-identification\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123720256.pdf)]\n\u003e ###### 24) *\"Unsupervised domain adaptation in the dissimilarity space for person re-identification\"* [[paper](https://arxiv.org/pdf/2007.13890.pdf)]\n\u003e ###### 25) *\"CycAs: Self-supervised Cycle Association for Learning Re-identifiable Descriptions\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123560069.pdf)]\n\n- \u003cins\u003e***Vehicle re-identification***\u003c/ins\u003e\n\u003e ###### 1) *\"Simulating Content Consistent Vehicle Datasets with Attribute Descent\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510766.pdf)]\n\u003e ###### 2) *\"The Devil is in the Details: Self-Supervised Attention for Vehicle Re-Identification\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123590358.pdf)]\n\u003e ###### 3) *\"Orientation-aware Vehicle Re-identification with Semantics-guided Part Attention Network\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123470324.pdf)]\n\n- \u003cins\u003e***Person search (detection + re-id)***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Online Multi-modal Person Search in Videos\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123570171.pdf)]\n\n- \u003cins\u003e***Person search (language or attribute)***\u003c/ins\u003e\n\n\u003e ###### 1) *\"ViTAA: Visual-Textual Attributes Alignment in Person Search by Natural Language\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123570392.pdf)]\n\u003e ###### 2) *\"Symbiotic Adversarial Learning for Attribute-Based Person Search\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123590222.pdf)]\n\n- \u003cins\u003e***Person image synthesis / generation***\u003c/ins\u003e\n\u003e ###### 1) *\"XingGAN for Person Image Generation\"* [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123700715.pdf)]\n\n\n\n---\n\n## CVPR2020\n\n- \u003cins\u003e***Person re-identification***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Hi-CMD: Hierarchical Cross-Modality Disentanglement for Visible-Infrared Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Choi_Hi-CMD_Hierarchical_Cross-Modality_Disentanglement_for_Visible-Infrared_Person_Re-Identification_CVPR_2020_paper.pdf)] [[github](https://github.com/bismex/HiCMD)] [[video](https://www.youtube.com/watch?v=da_4DxF0rGk\u0026feature=youtu.be)]\n\u003e ###### 2) *\"Transferable, Controllable, and Inconspicuous Adversarial Attacks on Person Re-identification With Deep Mis-Ranking\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Wang_Transferable_Controllable_and_Inconspicuous_Adversarial_Attacks_on_Person_Re-identification_With_CVPR_2020_paper.pdf)] [[github](https://github.com/whj363636/Adversarial-attack-on-Person-ReID-With-Deep-Mis-Ranking)]\n\u003e ###### 3) *\"Inter-Task Association Critic for Cross-Resolution Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Cheng_Inter-Task_Association_Critic_for_Cross-Resolution_Person_Re-Identification_CVPR_2020_paper.pdf)] \n\u003e ###### 4) *\"Learning Multi-Granular Hypergraphs for Video-Based Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Yan_Learning_Multi-Granular_Hypergraphs_for_Video-Based_Person_Re-Identification_CVPR_2020_paper.pdf)]\n\u003e ###### 5) *\"Online Joint Multi-Metric Adaptation From Frequent Sharing-Subset Mining for Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Zhou_Online_Joint_Multi-Metric_Adaptation_From_Frequent_Sharing-Subset_Mining_for_Person_CVPR_2020_paper.pdf)]\n\u003e ###### 6) *\"Style Normalization and Restitution for Generalizable Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Jin_Style_Normalization_and_Restitution_for_Generalizable_Person_Re-Identification_CVPR_2020_paper.pdf)]\n\u003e ###### 7) *\"Relation-Aware Global Attention for Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Zhang_Relation-Aware_Global_Attention_for_Person_Re-Identification_CVPR_2020_paper.pdf)] [[github](https://github.com/microsoft/Relation-Aware-Global-Attention-Networks)]\n\u003e ###### 8) *\"Spatial-Temporal Graph Convolutional Network for Video-Based Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Yang_Spatial-Temporal_Graph_Convolutional_Network_for_Video-Based_Person_Re-Identification_CVPR_2020_paper.pdf)]\n\u003e ###### 9) *\"Salience-Guided Cascaded Suppression Network for Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Chen_Salience-Guided_Cascaded_Suppression_Network_for_Person_Re-Identification_CVPR_2020_paper.pdf)]\n\u003e ###### 10) *\"Unsupervised Person Re-Identification via Softened Similarity Learning\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Lin_Unsupervised_Person_Re-Identification_via_Softened_Similarity_Learning_CVPR_2020_paper.pdf)] \n\u003e ###### 11) *\"Weakly Supervised Discriminative Feature Learning With State Information for Person Identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Yu_Weakly_Supervised_Discriminative_Feature_Learning_With_State_Information_for_Person_CVPR_2020_paper.pdf)] [[github](https://github.com/KovenYu/state-information)]\n\u003e ###### 12) *\"High-Order Information Matters: Learning Relation and Topology for Occluded Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Wang_High-Order_Information_Matters_Learning_Relation_and_Topology_for_Occluded_Person_CVPR_2020_paper.pdf)] [[github](https://github.com/wangguanan/HOReID)]\n\u003e ###### 13) *\"Unity Style Transfer for Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Liu_Unity_Style_Transfer_for_Person_Re-Identification_CVPR_2020_paper.pdf)] \n\u003e ###### 14) *\"AD-Cluster: Augmented Discriminative Clustering for Domain Adaptive Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Zhai_AD-Cluster_Augmented_Discriminative_Clustering_for_Domain_Adaptive_Person_Re-Identification_CVPR_2020_paper.pdf)] \n\u003e ###### 15) *\"Multi-Granularity Reference-Aided Attentive Feature Aggregation for Video-Based Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Zhang_Multi-Granularity_Reference-Aided_Attentive_Feature_Aggregation_for_Video-Based_Person_Re-Identification_CVPR_2020_paper.pdf)] \n\u003e ###### 16) *\"Smoothing Adversarial Domain Attack and P-Memory Reconsolidation for Cross-Domain Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Wang_Smoothing_Adversarial_Domain_Attack_and_P-Memory_Reconsolidation_for_Cross-Domain_Person_CVPR_2020_paper.pdf)]\n\u003e ###### 17) *\"Learning Longterm Representations for Person Re-Identification Using Radio Signals\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Fan_Learning_Longterm_Representations_for_Person_Re-Identification_Using_Radio_Signals_CVPR_2020_paper.pdf)] \n\u003e ###### 18) *\"Unsupervised Person Re-Identification via Multi-Label Classification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Wang_Unsupervised_Person_Re-Identification_via_Multi-Label_Classification_CVPR_2020_paper.pdf)] \n\u003e ###### 19) *\"Pose-Guided Visible Part Matching for Occluded Person ReID\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Gao_Pose-Guided_Visible_Part_Matching_for_Occluded_Person_ReID_CVPR_2020_paper.pdf)] [[github](https://github.com/hh23333/PVPM)]\n\u003e ###### 20) *\"Camera On-Boarding for Person Re-Identification Using Hypothesis Transfer Learning\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Ahmed_Camera_On-Boarding_for_Person_Re-Identification_Using_Hypothesis_Transfer_Learning_CVPR_2020_paper.pdf)] \n\u003e ###### 21) *\"Cross-Modality Person Re-Identification With Shared-Specific Feature Transfer\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Lu_Cross-Modality_Person_Re-Identification_With_Shared-Specific_Feature_Transfer_CVPR_2020_paper.pdf)] \n\u003e ###### 22) *\"Hierarchical Clustering With Hard-Batch Triplet Loss for Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Zeng_Hierarchical_Clustering_With_Hard-Batch_Triplet_Loss_for_Person_Re-Identification_CVPR_2020_paper.pdf)] \n\u003e ###### 23) *\"Real-World Person Re-Identification via Degradation Invariance Learning\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Huang_Real-World_Person_Re-Identification_via_Degradation_Invariance_Learning_CVPR_2020_paper.pdf)] \n\u003e ###### 24) *\"COCAS: A Large-Scale Clothes Changing Person Dataset for Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Yu_COCAS_A_Large-Scale_Clothes_Changing_Person_Dataset_for_Re-Identification_CVPR_2020_paper.pdf)] \n\n- \u003cins\u003e***Vehicle re-identification***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Parsing-Based View-Aware Embedding Network for Vehicle Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Meng_Parsing-Based_View-Aware_Embedding_Network_for_Vehicle_Re-Identification_CVPR_2020_paper.pdf)] \n\n- \u003cins\u003e***Person search (detection + re-id)***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Instance Guided Proposal Network for Person Search\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Dong_Instance_Guided_Proposal_Network_for_Person_Search_CVPR_2020_paper.pdf)]\n\u003e ###### 2) *\"Bi-Directional Interaction Network for Person Search\"*  [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Dong_Bi-Directional_Interaction_Network_for_Person_Search_CVPR_2020_paper.pdf)]\n\u003e ###### 3) *\"Robust Partial Matching for Person Search in the Wild\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Zhong_Robust_Partial_Matching_for_Person_Search_in_the_Wild_CVPR_2020_paper.pdf)] \n\u003e ###### 4) *\"TCTS: A Task-Consistent Two-Stage Framework for Person Search\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Wang_TCTS_A_Task-Consistent_Two-Stage_Framework_for_Person_Search_CVPR_2020_paper.pdf)]\n\u003e ###### 5) *\"Norm-Aware Embedding for Efficient Person Search\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Chen_Norm-Aware_Embedding_for_Efficient_Person_Search_CVPR_2020_paper.pdf)]\n\n\n- \u003cins\u003e***Person search (language or attribute)***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Cross-Modal Cross-Domain Moment Alignment Network for Person Search\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Jing_Cross-Modal_Cross-Domain_Moment_Alignment_Network_for_Person_Search_CVPR_2020_paper.pdf)]\n\n- \u003cins\u003e***Person image synthesis / generation***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Controllable Person Image Synthesis With Attribute-Decomposed GAN\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Men_Controllable_Person_Image_Synthesis_With_Attribute-Decomposed_GAN_CVPR_2020_paper.pdf)] [[github](https://github.com/menyifang/ADGAN)]\n\u003e ###### 2) *\"Deep Image Spatial Transformation for Person Image Generation\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Ren_Deep_Image_Spatial_Transformation_for_Person_Image_Generation_CVPR_2020_paper.pdf)] [[github](https://github.com/RenYurui/Global-Flow-Local-Attention)]\n\u003e ###### 3) *\"MISC: Multi-Condition Injection and Spatially-Adaptive Compositing for Conditional Person Image Synthesis\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2020/papers/Weng_MISC_Multi-Condition_Injection_and_Spatially-Adaptive_Compositing_for_Conditional_Person_Image_CVPR_2020_paper.pdf)]\n\n\n\n---\n\n## ICCV2019\n\n- \u003cins\u003e***Person re-identification***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Instance-Guided Context Rendering for Cross-Domain Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Chen_Instance-Guided_Context_Rendering_for_Cross-Domain_Person_Re-Identification_ICCV_2019_paper.pdf)]\n\u003e ###### 2) *\"Mixed High-Order Attention Network for Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Chen_Mixed_High-Order_Attention_Network_for_Person_Re-Identification_ICCV_2019_paper.pdf)]\n\u003e ###### 3) *\"Pose-Guided Feature Alignment for Occluded Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Miao_Pose-Guided_Feature_Alignment_for_Occluded_Person_Re-Identification_ICCV_2019_paper.pdf)]\n\u003e ###### 4) *\"Robust Person Re-Identification by Modelling Feature Uncertainty\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Yu_Robust_Person_Re-Identification_by_Modelling_Feature_Uncertainty_ICCV_2019_paper.pdf)]\n\u003e ###### 5) *\"Co-Segmentation Inspired Attention Networks for Video-Based Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Subramaniam_Co-Segmentation_Inspired_Attention_Networks_for_Video-Based_Person_Re-Identification_ICCV_2019_paper.pdf)]\n\u003e ###### 6) *\"RGB-Infrared Cross-Modality Person Re-Identification via Joint Pixel and Feature Alignment\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Wang_RGB-Infrared_Cross-Modality_Person_Re-Identification_via_Joint_Pixel_and_Feature_Alignment_ICCV_2019_paper.pdf)]\n\u003e ###### 7) *\"Beyond Human Parts: Dual Part-Aligned Representations for Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Guo_Beyond_Human_Parts_Dual_Part-Aligned_Representations_for_Person_Re-Identification_ICCV_2019_paper.pdf)]\n\u003e ###### 8) *\"Batch DropBlock Network for Person Re-Identification and Beyond\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Dai_Batch_DropBlock_Network_for_Person_Re-Identification_and_Beyond_ICCV_2019_paper.pdf)]\n\u003e ###### 9) *\"Omni-Scale Feature Learning for Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Zhou_Omni-Scale_Feature_Learning_for_Person_Re-Identification_ICCV_2019_paper.pdf)]\n\u003e ###### 10) *\"Auto-ReID: Searching for a Part-Aware ConvNet for Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Quan_Auto-ReID_Searching_for_a_Part-Aware_ConvNet_for_Person_Re-Identification_ICCV_2019_paper.pdf)]\n\u003e ###### 11) *\"Second-Order Non-Local Attention Networks for Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Xia_Second-Order_Non-Local_Attention_Networks_for_Person_Re-Identification_ICCV_2019_paper.pdf)]\n\u003e ###### 12) *\"Global-Local Temporal Representations for Video Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Li_Global-Local_Temporal_Representations_for_Video_Person_Re-Identification_ICCV_2019_paper.pdf)]\n\u003e ###### 13) *\"Spectral Feature Transformation for Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Luo_Spectral_Feature_Transformation_for_Person_Re-Identification_ICCV_2019_paper.pdf)]\n\u003e ###### 14) *\"Self-Similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Fu_Self-Similarity_Grouping_A_Simple_Unsupervised_Cross_Domain_Adaptation_Approach_for_ICCV_2019_paper.pdf)]\n\u003e ###### 15) *\"Deep Reinforcement Active Learning for Human-in-the-Loop Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Liu_Deep_Reinforcement_Active_Learning_for_Human-in-the-Loop_Person_Re-Identification_ICCV_2019_paper.pdf)]\n\u003e ###### 16) *\"View Confusion Feature Learning for Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Liu_View_Confusion_Feature_Learning_for_Person_Re-Identification_ICCV_2019_paper.pdf)]\n\u003e ###### 17) *\"MVP Matching: A Maximum-Value Perfect Matching for Mining Hard Samples, With Application to Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Sun_MVP_Matching_A_Maximum-Value_Perfect_Matching_for_Mining_Hard_Samples_ICCV_2019_paper.pdf)]\n\u003e ###### 18) *\"Unsupervised Person Re-Identification by Camera-Aware Similarity Consistency Learning\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Wu_Unsupervised_Person_Re-Identification_by_Camera-Aware_Similarity_Consistency_Learning_ICCV_2019_paper.pdf)]\n\u003e ###### 19) *\"Cross-Dataset Person Re-Identification via Unsupervised Pose Disentanglement and Adaptation\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Li_Cross-Dataset_Person_Re-Identification_via_Unsupervised_Pose_Disentanglement_and_Adaptation_ICCV_2019_paper.pdf)]\n\u003e ###### 20) *\"Discriminative Feature Learning With Consistent Attention Regularization for Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Zhou_Discriminative_Feature_Learning_With_Consistent_Attention_Regularization_for_Person_Re-Identification_ICCV_2019_paper.pdf)]\n\u003e ###### 21) *\"A Novel Unsupervised Camera-Aware Domain Adaptation Framework for Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Qi_A_Novel_Unsupervised_Camera-Aware_Domain_Adaptation_Framework_for_Person_Re-Identification_ICCV_2019_paper.pdf)]\n\u003e ###### 22) *\"Recover and Identify: A Generative Dual Model for Cross-Resolution Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Li_Recover_and_Identify_A_Generative_Dual_Model_for_Cross-Resolution_Person_ICCV_2019_paper.pdf)]\n\u003e ###### 23) *\"Self-Training With Progressive Augmentation for Unsupervised Cross-Domain Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Zhang_Self-Training_With_Progressive_Augmentation_for_Unsupervised_Cross-Domain_Person_Re-Identification_ICCV_2019_paper.pdf)]\n\u003e ###### 24) *\"Unsupervised Graph Association for Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Wu_Unsupervised_Graph_Association_for_Person_Re-Identification_ICCV_2019_paper.pdf)]\n\u003e ###### 25) *\"advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Wang_advPattern_Physical-World_Attacks_on_Deep_Person_Re-Identification_via_Adversarially_Transformable_ICCV_2019_paper.pdf)]\n\u003e ###### 26) *\"ABD-Net: Attentive but Diverse Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Chen_ABD-Net_Attentive_but_Diverse_Person_Re-Identification_ICCV_2019_paper.pdf)]\n\u003e ###### 27) *\"Foreground-Aware Pyramid Reconstruction for Alignment-Free Occluded Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/He_Foreground-Aware_Pyramid_Reconstruction_for_Alignment-Free_Occluded_Person_Re-Identification_ICCV_2019_paper.pdf)]\n\u003e ###### 28) *\"SBSGAN: Suppression of Inter-Domain Background Shift for Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Huang_SBSGAN_Suppression_of_Inter-Domain_Background_Shift_for_Person_Re-Identification_ICCV_2019_paper.pdf)]\n\u003e ###### 29) *\"Self-Critical Attention Learning for Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Chen_Self-Critical_Attention_Learning_for_Person_Re-Identification_ICCV_2019_paper.pdf)]\n\u003e ###### 30) *\"Temporal Knowledge Propagation for Image-to-Video Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Gu_Temporal_Knowledge_Propagation_for_Image-to-Video_Person_Re-Identification_ICCV_2019_paper.pdf)]\n\u003e ###### 31) *\"Deep Constrained Dominant Sets for Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Alemu_Deep_Constrained_Dominant_Sets_for_Person_Re-Identification_ICCV_2019_paper.pdf)]\n\u003e ###### 32) *\"Bilinear Attention Networks for Person Retrieval\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Fang_Bilinear_Attention_Networks_for_Person_Retrieval_ICCV_2019_paper.pdf)]\n\u003e ###### 33) *\"Deep Meta Metric Learning\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Chen_Deep_Meta_Metric_Learning_ICCV_2019_paper.pdf)]\n\n\n- \u003cins\u003e***Vehicle re-identification***\u003c/ins\u003e\n\n\u003e ###### 1) *\"PAMTRI: Pose-Aware Multi-Task Learning for Vehicle Re-Identification Using Highly Randomized Synthetic Data\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Tang_PAMTRI_Pose-Aware_Multi-Task_Learning_for_Vehicle_Re-Identification_Using_Highly_Randomized_ICCV_2019_paper.pdf)]\n\u003e ###### 2) *\"Vehicle Re-Identification in Aerial Imagery: Dataset and Approach\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Wang_Vehicle_Re-Identification_in_Aerial_Imagery_Dataset_and_Approach_ICCV_2019_paper.pdf)]\n\u003e ###### 3) *\"A Dual-Path Model With Adaptive Attention for Vehicle Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Khorramshahi_A_Dual-Path_Model_With_Adaptive_Attention_for_Vehicle_Re-Identification_ICCV_2019_paper.pdf)]\n\u003e ###### 4) *\"Vehicle Re-Identification With Viewpoint-Aware Metric Learning\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Chu_Vehicle_Re-Identification_With_Viewpoint-Aware_Metric_Learning_ICCV_2019_paper.pdf)]\n\n- \u003cins\u003e***Person search (detection + re-id)***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Re-ID Driven Localization Refinement for Person Search\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Han_Re-ID_Driven_Localization_Refinement_for_Person_Search_ICCV_2019_paper.pdf)]\n\n\n- \u003cins\u003e***Person search (language or attribute)***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Person Search by Text Attribute Query As Zero-Shot Learning\"* [[paper](http://openaccess.thecvf.com/content_ICCV_2019/papers/Dong_Person_Search_by_Text_Attribute_Query_As_Zero-Shot_Learning_ICCV_2019_paper.pdf)]\n\n\n\n---\n\n## CVPR2019\n\n- \u003cins\u003e***Person re-identification***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Weakly Supervised Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Meng_Weakly_Supervised_Person_Re-Identification_CVPR_2019_paper.pdf)]\n\u003e ###### 2) *\"Patch-Based Discriminative Feature Learning for Unsupervised Person Re-identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Yang_Patch-Based_Discriminative_Feature_Learning_for_Unsupervised_Person_Re-Identification_CVPR_2019_paper.pdf)] [[github]](https://github.com/QizeYang/PAUL)\n\u003e ###### 3) *\"Unsupervised Person Re-identification by Soft Multilabel Learning\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Yu_Unsupervised_Person_Re-Identification_by_Soft_Multilabel_Learning_CVPR_2019_paper.pdf)] [[github](https://github.com/KovenYu/MAR)]\n\u003e ###### 4) *\"Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Zhong_Invariance_Matters_Exemplar_Memory_for_Domain_Adaptive_Person_Re-Identification_CVPR_2019_paper.pdf)] [[github](https://github.com/zhunzhong07/ECN)]\n\u003e ###### 5) *\"Adaptive Transfer Network for Cross-Domain Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Liu_Adaptive_Transfer_Network_for_Cross-Domain_Person_Re-Identification_CVPR_2019_paper.pdf)]\n\u003e ###### 6) *\"Densely Semantically Aligned Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Zhang_Densely_Semantically_Aligned_Person_Re-Identification_CVPR_2019_paper.pdf)]\n\u003e ###### 7) *\"Generalizable Person Re-identification by Domain-Invariant Mapping Network\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Song_Generalizable_Person_Re-Identification_by_Domain-Invariant_Mapping_Network_CVPR_2019_paper.pdf)]\n\u003e ###### 8) *\"Re-Identification with Consistent Attentive Siamese Networks\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Zheng_Re-Identification_With_Consistent_Attentive_Siamese_Networks_CVPR_2019_paper.pdf)]\n\u003e ###### 9) *\"Distilled Person Re-identification: Towards a More Scalable System\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Wu_Distilled_Person_Re-Identification_Towards_a_More_Scalable_System_CVPR_2019_paper.pdf)]\n\u003e ###### 10) *\"Towards Rich Feature Discovery with Class Activation Maps Augmentation for Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Yang_Towards_Rich_Feature_Discovery_With_Class_Activation_Maps_Augmentation_for_CVPR_2019_paper.pdf)]\n\u003e ###### 11) *\"AANet: Attribute Attention Network for Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Tay_AANet_Attribute_Attention_Network_for_Person_Re-Identifications_CVPR_2019_paper.pdf)]\n\u003e ###### 12) *\"Pyramidal Person Re-IDentification via Multi-Loss Dynamic Training\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Zheng_Pyramidal_Person_Re-IDentification_via_Multi-Loss_Dynamic_Training_CVPR_2019_paper.pdf)]\n\u003e ###### 13) *\"Interaction-and-Aggregation Network for Person Re-identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Hou_Interaction-And-Aggregation_Network_for_Person_Re-Identification_CVPR_2019_paper.pdf)]\n\u003e ###### 14) *\"Perceive Where to Focus: Learning Visibility-aware Part-level Features for Partial Person Re-identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Sun_Perceive_Where_to_Focus_Learning_Visibility-Aware_Part-Level_Features_for_Partial_CVPR_2019_paper.pdf)]\n\u003e ###### 15) *\"VRSTC: Occlusion-Free Video Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Hou_VRSTC_Occlusion-Free_Video_Person_Re-Identification_CVPR_2019_paper.pdf)]\n\u003e ###### 16) *\"Attribute-Driven Feature Disentangling and Temporal Aggregation for Video Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Zhao_Attribute-Driven_Feature_Disentangling_and_Temporal_Aggregation_for_Video_Person_Re-Identification_CVPR_2019_paper.pdf)]\n\u003e ###### 17) *\"Learning to Reduce Dual-level Discrepancy for Infrared-Visible Person Re-identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Wang_Learning_to_Reduce_Dual-Level_Discrepancy_for_Infrared-Visible_Person_Re-Identification_CVPR_2019_paper.pdf)]\n\u003e ###### 18) *\"Joint Discriminative and Generative Learning for Person Re-identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Zheng_Joint_Discriminative_and_Generative_Learning_for_Person_Re-Identification_CVPR_2019_paper.pdf)] [[github](https://github.com/NVlabs/DG-Net)]\n\u003e ###### 19) *\"Re-Identification Supervised Texture Generation\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Wang_Re-Identification_Supervised_Texture_Generation_CVPR_2019_paper.pdf)]\n\u003e ###### 20) *\"Re-ranking via Metric Fusion for Object Retrieval and Person Re-identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Bai_Re-Ranking_via_Metric_Fusion_for_Object_Retrieval_and_Person_Re-Identification_CVPR_2019_paper.pdf)]\n\u003e ###### 21) *\"Dissecting Person Re-identification from the Viewpoint of Viewpoint\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Sun_Dissecting_Person_Re-Identification_From_the_Viewpoint_of_Viewpoint_CVPR_2019_paper.pdf)] [[github](https://github.com/sxzrt/Dissecting-Person-Re-ID-from-the-Viewpoint-of-Viewpoint)]\n\n- \u003cins\u003e***Vehicle re-identification***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Part-regularized Near-Duplicate Vehicle Re-identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/He_Part-Regularized_Near-Duplicate_Vehicle_Re-Identification_CVPR_2019_paper.pdf)]\n\u003e ###### 2) *\"CityFlow: A City-Scale Benchmark for Multi-Target Multi-Camera Vehicle Tracking and Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Tang_CityFlow_A_City-Scale_Benchmark_for_Multi-Target_Multi-Camera_Vehicle_Tracking_and_CVPR_2019_paper.pdf)]\n\u003e ###### 3) *\"VERI-Wild: A Large Dataset and a New Method for Vehicle Re-Identification in the Wild\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Lou_VERI-Wild_A_Large_Dataset_and_a_New_Method_for_Vehicle_CVPR_2019_paper.pdf)]\n\n- \u003cins\u003e***Person search (detection + re-id)***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Query-guided End-to-End Person Search\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Munjal_Query-Guided_End-To-End_Person_Search_CVPR_2019_paper.pdf)] [[github](https://github.com/munjalbharti/Query-guided-End-to-End-Person-Search)]\n\u003e ###### 2) *\"Learning Context Graph for Person Search\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Yan_Learning_Context_Graph_for_Person_Search_CVPR_2019_paper.pdf)] [[github](https://github.com/sjtuzq/person_search_gcn)]\n\n- \u003cins\u003e***Person image synthesis / generation***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Progressive Pose Attention Transfer for Person Image Generation\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Zhu_Progressive_Pose_Attention_Transfer_for_Person_Image_Generation_CVPR_2019_paper.pdf)] [[github](https://github.com/tengteng95/Pose-Transfer)]\n\u003e ###### 2) *\"Unsupervised Person Image Generation with Semantic Parsing Transformation\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Song_Unsupervised_Person_Image_Generation_With_Semantic_Parsing_Transformation_CVPR_2019_paper.pdf)] [[github](https://github.com/SijieSong/person_generation_spt)]\n\u003e ###### 3) *\"Text Guided Person Image Synthesis\"* [[paper](http://openaccess.thecvf.com/content_CVPR_2019/papers/Zhou_Text_Guided_Person_Image_Synthesis_CVPR_2019_paper.pdf)]\n\n\n\n---\n\n## ECCV2018\n\n- \u003cins\u003e***Person re-identification***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Domain Adaptation through Synthesis for Unsupervised Person Re-identification\"* [[paper](http://openaccess.thecvf.com/content_ECCV_2018/papers/Slawomir_Bak_Domain_Adaptation_through_ECCV_2018_paper.pdf)]\n\u003e ###### 2) *\"Unsupervised Person Re-identification by Deep Learning Tracklet Association\"* [[paper](http://openaccess.thecvf.com/content_ECCV_2018/papers/Minxian_Li_Unsupervised_Person_Re-identification_ECCV_2018_paper.pdf)]\n\u003e ###### 3) *\"Generalizing A Person Retrieval Model Hetero- and Homogeneously\"* [[paper](http://openaccess.thecvf.com/content_ECCV_2018/papers/Zhun_Zhong_Generalizing_A_Person_ECCV_2018_paper.pdf)] [[Github](https://github.com/zhunzhong07/HHL)]\n\u003e ###### 4) *\"Robust Anchor Embedding for Unsupervised Video Person Re-Identification in the Wild\"* [[paper](http://openaccess.thecvf.com/content_ECCV_2018/papers/Mang_YE_Robust_Anchor_Embedding_ECCV_2018_paper.pdf)]\n\u003e ###### 5) *\"Maximum Margin Metric Learning Over Discriminative Nullspace for Person Re-identification\"* [[paper](http://openaccess.thecvf.com/content_ECCV_2018/papers/T_M_Feroz_Ali_Maximum_Margin_Metric_ECCV_2018_paper.pdf)]\n\u003e ###### 6) *\"Person Re-identification with Deep Similarity-Guided Graph Neural Network\"* [[paper](http://openaccess.thecvf.com/content_ECCV_2018/papers/Yantao_Shen_Person_Re-identification_with_ECCV_2018_paper.pdf)]\n\u003e ###### 7) *\"Pose-Normalized Image Generation for Person Re-identification\"* [[paper](http://openaccess.thecvf.com/content_ECCV_2018/papers/Xuelin_Qian_Pose-Normalized_Image_Generation_ECCV_2018_paper.pdf)]\n\u003e ###### 8) *\"Improving Deep Visual Representation for Person Re-identification by Global and Local Image-language Association\"* [[paper](http://openaccess.thecvf.com/content_ECCV_2018/papers/Dapeng_Chen_Improving_Deep_Visual_ECCV_2018_paper.pdf)]\n\u003e ###### 9) *\"Hard-Aware Point-to-Set Deep Metric for Person Re-identification\"* [[paper](http://openaccess.thecvf.com/content_ECCV_2018/papers/Rui_Yu_Hard-Aware_Point-to-Set_Deep_ECCV_2018_paper.pdf)]\n\u003e ###### 10) *\"Part-Aligned Bilinear Representations for Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ECCV_2018/papers/Yumin_Suh_Part-Aligned_Bilinear_Representations_ECCV_2018_paper.pdf)] [[Github](https://github.com/yuminsuh/part_bilinear_reid)]\n\u003e ###### 11) *\"Mancs: A Multi-task Attentional Network with Curriculum Sampling for Person Re-identification\"* [[paper](http://openaccess.thecvf.com/content_ECCV_2018/papers/Cheng_Wang_Mancs_A_Multi-task_ECCV_2018_paper.pdf)]\n\u003e ###### 12) *\"Beyond Part Models: Person Retrieval with Refined Part Pooling (and A Strong Convolutional Baseline)\"* [[paper](http://openaccess.thecvf.com/content_ECCV_2018/papers/Yifan_Sun_Beyond_Part_Models_ECCV_2018_paper.pdf)]\n\u003e ###### 13) *\"Reinforced Temporal Attention and Split-Rate Transfer for Depth-Based Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ECCV_2018/papers/Nikolaos_Karianakis_Reinforced_Temporal_Attention_ECCV_2018_paper.pdf)]\n\u003e ###### 14) *\"Adversarial Open-World Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_ECCV_2018/papers/Xiang_Li_Adversarial_Open-World_Person_ECCV_2018_paper.pdf)]\n\u003e ###### 15) *\"Integrating Egocentric Videos in Top-view Surveillance Videos: Joint Identification and Temporal Alignment\"* [[paper](http://openaccess.thecvf.com/content_ECCV_2018/papers/Shervin_Ardeshir_Integrating_Egocentric_Videos_ECCV_2018_paper.pdf)]\n\n- \u003cins\u003e***Person search (detection + re-id)***\u003c/ins\u003e\n\n\u003e ###### 1) *\"RCAA: Relational Context-Aware Agents for Person Search\"* [[paper](http://openaccess.thecvf.com/content_ECCV_2018/papers/Xiaojun_Chang_RCAA_Relational_Context-Aware_ECCV_2018_paper.pdf)]\n\u003e ###### 2) *\"Person Search in Videos with One Portrait Through Visual and Temporal Links\"* [[paper](http://openaccess.thecvf.com/content_ECCV_2018/papers/Qingqiu_Huang_Person_Search_in_ECCV_2018_paper.pdf)]\n\u003e ###### 3) *\"Person Search by Multi-Scale Matching\"* [[paper](http://openaccess.thecvf.com/content_ECCV_2018/papers/Xu_Lan_Person_Search_by_ECCV_2018_paper.pdf)]\n\u003e ###### 4) *\"Person Search via A Mask-Guided Two-Stream CNN Model\"* [[paper](http://openaccess.thecvf.com/content_ECCV_2018/papers/Di_Chen_Person_Search_via_ECCV_2018_paper.pdf)]\n\n\n\n\n---\n\n## CVPR2018\n\n- \u003cins\u003e***Person re-identification***\u003c/ins\u003e\n\n\u003e ###### 1) *\"Unsupervised Cross-dataset Person Re-identification by Transfer Learning of Spatial-Temporal Patterns\"* [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Lv_Unsupervised_Cross-Dataset_Person_CVPR_2018_paper.pdf)] [[Github](https://github.com/ahangchen/TFusion)]\n\u003e ###### 2) *\"Transferable Joint Attribute-Identity Deep Learning for Unsupervised Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Transferable_Joint_Attribute-Identity_CVPR_2018_paper.pdf)]\n\u003e ###### 3) *\"Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification\"* [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Deng_Image-Image_Domain_Adaptation_CVPR_2018_paper.pdf)] [[Github](https://github.com/Simon4Yan/Learning-via-Translation)]\n\u003e ###### 4) *\"Disentangled Person Image Generation\"* [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Ma_Disentangled_Person_Image_CVPR_2018_paper.pdf)]\n\u003e ###### 5) *\"Exploit the Unknown Gradually: One-Shot Video-Based Person Re-Identification by Stepwise Learning\"* [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wu_Exploit_the_Unknown_CVPR_2018_paper.pdf)] [[Github](https://github.com/Yu-Wu/Exploit-Unknown-Gradually)] [[Homepage](https://yu-wu.net/publication/cvpr2018-oneshot-reid/)]\n\u003e ###### 6) *\"Diversity Regularized Spatiotemporal Attention for Video-based Person Re-identification\"* [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Diversity_Regularized_Spatiotemporal_CVPR_2018_paper.pdf)]\n\u003e ###### 7) *\"A Pose-Sensitive Embedding for Person Re-Identification with Expanded Cross Neighborhood Re-Ranking\"* [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Sarfraz_A_Pose-Sensitive_Embedding_CVPR_2018_paper.pdf)]\n\u003e ###### 8) *\"Human Semantic Parsing for Person Re-identification\"* [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Kalayeh_Human_Semantic_Parsing_CVPR_2018_paper.pdf)]\n\u003e ###### 9) *\"Video Person Re-identification with Competitive Snippet-similarity Aggregation and Co-attentive Snippet Embedding\"* [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Video_Person_Re-Identification_CVPR_2018_paper.pdf)]\n\u003e ###### 10) *\"Mask-guided Contrastive Attention Model for Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Song_Mask-Guided_Contrastive_Attention_CVPR_2018_paper.pdf)]\n\u003e ###### 11) *\"Person Re-identification with Cascaded Pairwise Convolutions\"* [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Wang_Person_Re-Identification_With_CVPR_2018_paper.pdf)]\n\u003e ###### 12) *\"Multi-Level Factorisation Net for Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chang_Multi-Level_Factorisation_Net_CVPR_2018_paper.pdf)]\n\u003e ###### 13) *\"Attention-Aware Compositional Network for Person Re-identification\"* [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Xu_Attention-Aware_Compositional_Network_CVPR_2018_paper.pdf)]\n\u003e ###### 14) *\"Deep Group-shuffling Random Walk for Person Re-identification\"* [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Shen_Deep_Group-Shuffling_Random_CVPR_2018_paper.pdf)]\n\u003e ###### 15) *\"Harmonious Attention Network for Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Li_Harmonious_Attention_Network_CVPR_2018_paper.pdf)]\n\u003e ###### 16) *\"Efficient and Deep Person Re-Identification using Multi-Level Similarity\"* [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Guo_Efficient_and_Deep_CVPR_2018_paper.pdf)]\n\u003e ###### 17) *\"Pose Transferrable Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Liu_Pose_Transferrable_Person_CVPR_2018_paper.pdf)]\n\u003e ###### 18) *\"Adversarially Occluded Samples for Person Re-identification\"* [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Huang_Adversarially_Occluded_Samples_CVPR_2018_paper.pdf)]\n\u003e ###### 19) *\"Camera Style Adaptation for Person Re-identification\"* [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhong_Camera_Style_Adaptation_CVPR_2018_paper.pdf)]\n\u003e ###### 20) *\"Dual Attention Matching Network for Context-Aware Feature Sequence based Person Re-Identification\"* [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Si_Dual_Attention_Matching_CVPR_2018_paper.pdf)]\n\u003e ###### 21) *\"Easy Identification from Better Constraints: Multi-Shot Person Re-Identification from Reference Constraints\"* [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Zhou_Easy_Identification_From_CVPR_2018_paper.pdf)]\n\u003e ###### 22) *\"Eliminating Background-bias for Robust Person Re-identification\"* [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Tian_Eliminating_Background-Bias_for_CVPR_2018_paper.pdf)]\n\u003e ###### 23) *\"Features for Multi-Target Multi-Camera Tracking and Re-Identification\"* 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