{"id":45541,"url":"https://github.com/visionxiang/awesome-salient-object-detection","name":"awesome-salient-object-detection","description":"A curated list of awesome resources for salient object detection (SOD), focusing more on multi-modal SOD, such as RGB-D SOD.","projects_count":117,"last_synced_at":"2026-10-19T21:00:17.750Z","repository":{"id":40739818,"uuid":"409765346","full_name":"visionxiang/awesome-salient-object-detection","owner":"visionxiang","description":"A curated list of awesome resources for salient object detection (SOD), focusing more on multi-modal SOD, such as RGB-D SOD.","archived":false,"fork":false,"pushed_at":"2024-09-26T12:39:17.000Z","size":84,"stargazers_count":148,"open_issues_count":0,"forks_count":8,"subscribers_count":4,"default_branch":"main","last_synced_at":"2026-09-30T07:07:31.338Z","etag":null,"topics":["multimodal","object-segmentation","rgbd-sod","salient-object-detection","sod"],"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/visionxiang.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,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2021-09-23T22:54:16.000Z","updated_at":"2026-08-29T08:37:04.000Z","dependencies_parsed_at":"2025-12-08T11:00:56.641Z","dependency_job_id":null,"html_url":"https://github.com/visionxiang/awesome-salient-object-detection","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/visionxiang/awesome-salient-object-detection","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/visionxiang%2Fawesome-salient-object-detection","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/visionxiang%2Fawesome-salient-object-detection/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/visionxiang%2Fawesome-salient-object-detection/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/visionxiang%2Fawesome-salient-object-detection/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/visionxiang","download_url":"https://codeload.github.com/visionxiang/awesome-salient-object-detection/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/visionxiang%2Fawesome-salient-object-detection/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":344872684,"owners_count":38372451,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-10-03T21:59:58.778Z","status":"online","status_checked_at":"2026-10-19T02:00:06.414Z","response_time":53,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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"}},"created_at":"2024-01-13T21:19:09.967Z","updated_at":"2026-10-19T21:00:17.750Z","primary_language":null,"list_of_lists":false,"displayable":true,"categories":["Image SOD","RGB-D SOD","Overview","RGB-T SOD","V-D-T SOD","Appendix"],"sub_categories":["Beyond","2021","2023","2019","2022","2024","2020","Preprint"],"readme":"# Salient Object Detection\n\n🔥 A curated list of awesome resources for salient object detection (SOD), focusing more on multi-modal SODs (e.g., RGB-D/RGB-T SOD).\n\n:heavy_exclamation_mark:Updated at 2024-06-19.\n\n\n--------------------------------------------------------------------------------------\n\n\u003c!--TOC--\u003e\n\n## Content:\n- [Overview](#Overview)\n- [RGB-D SOD](#RGB-D-SOD)\n- [RGB-T SOD](#RGB-T-SOD)\n- [V-D-T SOD](#V-D-T-SOD)\n- [Image SOD](#Image-SOD)\n- [Appendix](#Appendix)\n\n--------------------------------------------------------------------------------------\n\n\n\n## Overview\n\n| **Year** | **Pub.** | **Title**                                      | **Links**                                              |\n| :------: | :------: | :--------------------------------------- | :----------------------------------------------------------- |\n|   2020   |   CVM    | RGB-D Salient Object Detection: A Survey \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Tao Zhou, Deng-Ping Fan, Ming-Ming Cheng, Jianbing Shen, Ling Shao*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://arxiv.org/abs/2008.00230)/[Proj](https://github.com/taozh2017/RGBD-SODsurvey) |\n\n\n\n\n## RGB-D SOD\n\n### Preprint\n\n| **Year** | **Pub.** | **Title**              | **Links**                                                    |\n| :------: | :------- | :----------------------------------------------------------- | :------------------------------------------------------------ |\n|   2023  | arXiv | All in One: RGB, RGB-D, and RGB-T Salient Object Detection   \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Xingzhao Jia, Zhongqiu Zhao, Changlei Dongye, Zhao Zhang*\u003c/sup\u003e\u003c/sub\u003e   | [Paper](https://arxiv.org/abs/2311.14746)/Code \n\n\n\n### 2024\n\n| **Year** | **Pub.** | **Title** |  **Links**                                       |\n| :-----: | :------: | :----------------------------------------------------------- |   :----------------------------------------------------------- |\n| 2024  | AppSci | Advancing in RGB-D Salient Object Detection: A Survey   \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Ai Chen, Xin Li, Tianxiang He, Junlin Zhou, and Duanbing Chen*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://www.mdpi.com/2076-3417/14/17/8078)/Code \n| 2024  | IJCV  |  ViDSOD-100: A New Dataset and a Baseline Model for RGB-D Video Salient Object Detection  \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Junhao Lin, Lei Zhu, Jiaxing Shen, Huazhu Fu, Qing Zhang \u0026 Liansheng Wang*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://arxiv.org/abs/2406.12536v1)/[Code](https://github.com/jhl-Det/RGBD_Video_SOD) \n|  2024   | TNNLS | EM-Trans: Edge-Aware Multimodal Transformer for RGB-D Salient Object Detection   \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Geng Chen; Qingyue Wang; Bo Dong; Ruitao Ma; Nian Liu; Huazhu Fu; Yong Xia*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://ieeexplore.ieee.org/abstract/document/10433541)/Code\n|   2024   |  PAMI | Robust Perception and Precise Segmentation for Scribble-Supervised RGB-D Saliency Detection   \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Long Li, Junwei Han, Nian Liu, Salman Khan, Hisham Cholakkal, Rao Muhammad Anwer, Fahad Shahbaz Khan*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://ieeexplore.ieee.org/document/10288361)/Code\n|   2024  | KBS | MAGNet: Multi-scale Awareness and Global fusion Network for RGB-D salient object detection  \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Mingyu Zhong, Jing Sun, Peng Ren, Fasheng Wang, Fuming Sun*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://www.sciencedirect.com/science/article/abs/pii/S0950705124007603)/[Code](https://github.com/mingyu6346/MAGNet)\n|   2024   |  TCSVT | Mutual Information Regularization for Weakly-Supervised RGB-D Salient Object Detection   \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Aixuan Li; Yuxin Mao; Jing Zhang; Yuchao Dai*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://ieeexplore.ieee.org/document/10148985)/[Code](https://npucvr.github.io/MIRV/)\n|   2024   |  TCSVT | Feature Calibrating and Fusing Network for RGB-D Salient Object Detection   \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Qiang Zhang; Qi Qin; Yang Yang; Qiang Jiao; Jungong Han*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://ieeexplore.ieee.org/abstract/document/10185946)/Code\n\n\n### 2023\n\n| **Year** | **Pub.** | **Title** |  **Links**                                       |\n| :-----: | :------: | :----------------------------------------------------------- |   :----------------------------------------------------------- |\n|   2023  |  ACM MM  |  Object Segmentation by Mining Cross-Modal Semantics    \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Wu, Zongwei and Wang, Jingjing and Zhou, Zhuyun and An, Zhaochong and Jiang, Qiuping and Demonceaux, C{\\'e}dric and Sun, Guolei and Timofte, Radu*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://arxiv.org/abs/2305.10469)/[Code](https://github.com/Zongwei97/XMSNet)\n|   2023  |  ICCV  | Source-free depth for object pop-out     \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Wu, Zongwei and Paudel, Danda Pani and Fan, Deng-Ping and Wang, Jingjing and Wang, Shuo and Demonceaux, Cédric and Timofte, Radu and Van Gool, Luc*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://arxiv.org/abs/2212.05370)/[Code](https://github.com/Zongwei97/PopNet)\n|   2023   |  TIP  | CAVER: Cross-Modal View-Mixed Transformer for Bi-Modal Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Youwei Pang, Xiaoqi Zhao, Lihe Zhang, Huchuan Lu*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://arxiv.org/abs/2112.02363v3)/[Code](https://github.com/lartpang/CAVER) \n|   2023   | TIP   | HiDAnet: RGB-D Salient Object Detection via Hierarchical Depth Awareness    \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Wu, Zongwei and Allibert, Guillaume and Meriaudeau, Fabrice and Ma, Chao and Demonceaux, Cédric*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://arxiv.org/abs/2301.07405)/[Code](https://github.com/Zongwei97/HIDANet)\n|   2023   |  IJCV | Delving into Calibrated Depth for Accurate RGB-D Salient Object Detection   \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Jingjing Li, Wei Ji, Miao Zhang, Yongri Piao, Huchuan Lu, Li Cheng*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://link.springer.com/article/10.1007/s11263-022-01734-1)/Code\n|   2023   |  PR  | Cross-modal hierarchical interaction network for RGB-D salient object detection   \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Hongbo Bi a, Ranwan Wu a, Ziqi Liu a, Huihui Zhu a, Cong Zhang a, Tian-Zhu Xiang*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://www.sciencedirect.com/science/article/abs/pii/S0031320322006732)/[Code](https://github.com/RanwanWu/HINet)\n|   2023   |  TMM | CATNet: A Cascaded and Aggregated Transformer Network for RGB-D Salient Object Detection    \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Fuming Sun; Peng Ren; Bowen Yin; Fasheng Wang; Haojie Li*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://ieeexplore.ieee.org/document/10179145)/Code\n|   2023   |  TMM | Transformer Fusion and Pixel-Level Contrastive Learning for RGB-D Salient Object Detection   \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Jiesheng Wu; Fangwei Hao; Weiyun Liang; Jing Xu*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://ieeexplore.ieee.org/document/10122979)/Code\n|   2023   |  TMM | S3Net: Self-Supervised Self-Ensembling Network for Semi-Supervised RGB-D Salient Object Detection  \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Lei Zhu; Xiaoqiang Wang; Ping Li; Xin Yang; Qing Zhang; Weiming Wang; Carola-Bibiane Schönlieb; C. L. Philip Chen*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://ieeexplore.ieee.org/abstract/document/9623466)/Code\n|   2023  | Neurocom | Dual Swin-Transformer based Mutual Interactive Network for RGB-D Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Chao Zeng, Sam Kwong*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://arxiv.org/abs/2206.03105)/Code\n\n\n\n### 2022 \n\n| **Year** | **Pub.** | **Title** |  **Links**                                       |\n| :-----: | :------: | :----------------------------------------------------------- |   :----------------------------------------------------------- |\n|   2022   |  MM | Depth-inspired Label Mining for Unsupervised RGB-D Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Teng Yang, Yue Wang, Lu Zhang, Jinqing Qi, Huchuan Lu*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://dl.acm.org/doi/10.1145/3503161.3548037)/[Code](https://github.com/youngtboy/DLM)\n|   2022   |  ECCV | MVSalNet: Multi-View Augmentation for RGB-D Salient Object Detection  \u003cbr\u003e \u003csub\u003e\u003csup\u003e*JiaYuan Zhou, Lijun Wang, Huchuan Lu, Kaining Huang, Xinchu Shi, Bocong Liu*\u003c/sup\u003e\u003c/sub\u003e | Paper/[Code](https://github.com/Heart-eartH/MVSalNet) |\n|   2022   |  ECCV | SPSN: Superpixel Prototype Sampling Network for RGB-D Salient Object Detection  \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Minhyeok Lee, Chaewon Park, Suhwan Cho, Sangyoun Lee*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://arxiv.org/abs/2207.07898)/[Code](https://github.com/Hydragon516/SPSN)\n|   2022   |  AAAI | Self-Supervised Pretraining for RGB-D Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Xiaoqi Zhao, Youwei Pang, Lihe Zhang, Huchuan Lu, Xiang Ruan*\u003c/sup\u003e\u003c/sub\u003e     | [Paper](https://arxiv.org/pdf/2101.12482.pdf)/[Code](https://github.com/Xiaoqi-Zhao-DLUT/SSLSOD) |\n|   2022   | ICLR | Promoting Saliency From Depth: Deep Unsupervised RGB-D Saliency Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Wei Ji, Jingjing Li, Qi Bi, Chuan Guo, Jie Liu, Li Cheng*\u003c/sup\u003e\u003c/sub\u003e  | [Paper](https://openreview.net/pdf?id=BZnnMbt0pW)/[Code](https://github.com/jiwei0921/DSU)\n|      ---     |    ---      |    ---       |     ---      |\n|   2022   | IJCV  | Learnable Depth-Sensitive Attention for Deep RGB-D Saliency Detection with Multi-modal Fusion Architecture Search \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Peng Sun, Wenhu Zhang, Songyuan Li, Yilin Guo, Congli Song \u0026 Xi Li*\u003c/sup\u003e\u003c/sub\u003e  | [Paper](https://link.springer.com/article/10.1007/s11263-022-01646-0?utm_source=toc\u0026utm_medium=email\u0026utm_campaign=toc_11263_130_11\u0026utm_content=etoc_springer_20221001)/Code\n|   2022   |  PAMI | Learning Selective Mutual Attention and Contrast for RGB-D Saliency Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Nian Liu, Ni Zhang, Ling Shao, Junwei Han*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://arxiv.org/abs/2010.05537)/[Code](https://github.com/nnizhang/SMAC)\n|   2022   |  TMM  | C2DFNet: Criss-Cross Dynamic Filter Network for RGB-D Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Miao Zhang, et al.*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://ieeexplore.ieee.org/abstract/document/9813422)/[Code](https://github.com/OIPLab-DUT/C2DFNet)\n|   2022   |  TIP  | Boosting RGB-D Saliency Detection by Leveraging Unlabeled RGB Images  \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Xiaoqiang Wang, et al.*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://arxiv.org/abs/2201.00100)/Code\n|   2022   |  TIP  | Middle-level Fusion for Lightweight RGB-D Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*N. Huang, Qiang Jiao, Qiang Zhang, Jungong Han*\u003c/sup\u003e\u003c/sub\u003e          | [Paper](https://arxiv.org/pdf/2104.11543.pdf)/Code           |\n\n\n\n### 2021\n\n| **Year** | **Pub.** | **Title**   | **Links**                                      |\n| :-----: | :------: | :----------------------------------------------------------- | :----------------------------------------------------------- |\n|   2021    | NeurIPS  | Joint Semantic Mining for Weakly Supervised RGB-D Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Jingjing Li1, Wei Ji, Qi Bi, Cheng Yan, Miao Zhang, Yongri Piao, Huchuan Lu, Li Cheng*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://proceedings.neurips.cc/paper/2021/file/642e92efb79421734881b53e1e1b18b6-Paper.pdf)/[Code](https://github.com/jiwei0921/JSM) |\n|   2021    |   ICCV   | Visual Saliency Transformer       \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Nian Liu, Junwei Han, et al.*\u003c/sup\u003e\u003c/sub\u003e  | [Paper](https://arxiv.org/pdf/2104.12099.pdf)/[Code](https://github.com/nnizhang/VST#visual-saliency-transformer-vst) |\n|   2021    |   ICCV   | Specificity-preserving RGB-D Saliency Detection   \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Tao Zhou, et al.*\u003c/sup\u003e\u003c/sub\u003e  | [Paper](https://arxiv.org/abs/2108.08162)/[Code](https://github.com/taozh2017/SPNet) |\n|   2021    |   ICCV   | RGB-D Saliency Detection via Cascaded Mutual Information Minimization \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Jing Zhang, Deng-Ping Fan, et al.*\u003c/sup\u003e\u003c/sub\u003e    | [Paper](https://arxiv-download.xixiaoyao.cn/pdf/2109.07246.pdf)/[Code](https://github.com/JingZhang617/cascaded_rgbd_sod) |\n|   2021    |    MM    | Depth Quality-Inspired Feature Manipulation for Efficient RGB-D Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Wenbo Zhang, Keren Fu, et al.*\u003c/sup\u003e\u003c/sub\u003e    | [Paper](https://arxiv.org/abs/2107.01779)/[Code](https://github.com/zwbx/DFM-Net) |\n|   2021    |    MM    | Cross-modality Discrepant Interaction Network for RGB-D Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Chen Zhang, Runmin Cong, et al.*\u003c/sup\u003e\u003c/sub\u003e   | [Paper](https://arxiv.org/abs/2108.01971)/[Proj](https://rmcong.github.io/proj_CDINet.html?utm_source=catalyzex.com) |\n|   2021    |    MM    | TriTransNet: RGB-D salient object detection with a triplet transformer embedding network \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Zhengyi Liu, et al.*\u003c/sup\u003e\u003c/sub\u003e   | [Paper](https://arxiv.org/abs/2108.03990)/Code    |\n|   2021    |   CVPR   | Deep RGB-D Saliency Detection With Depth-Sensitive Attention and Automatic Multi-Modal Fusion \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Peng Sun, Xi Li, et al.*\u003c/sup\u003e\u003c/sub\u003e   | [Paper](https://arxiv.org/abs/2103.11832)/[Code](https://github.com/sunpeng1996/DSA2F)\u003cbr\u003e[IJCV](https://link.springer.com/article/10.1007/s11263-022-01646-0) |\n|   2021    |   CVPR   | Calibrated RGB-D Salient Object Detection     \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Wei Ji, Shuang Yu, et al.*\u003c/sup\u003e\u003c/sub\u003e   | [Paper](https://openaccess.thecvf.com/content/CVPR2021/papers/Ji_Calibrated_RGB-D_Salient_Object_Detection_CVPR_2021_paper.pdf)/[Code](https://github.com/jiwei0921/DCF) |\n|   2021    |   ICME   | BTS-Net: Bi-directional Transfer-and-Selection Network For RGB-D Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Wenbo Zhang, Keren Fu, et al.*\u003c/sup\u003e\u003c/sub\u003e     | [arXiv](https://arxiv.org/pdf/2104.01784.pdf)/[Code](https://github.com/zwbx/BTS-Net) |\n|   2021    |   AAAI   | RGB-D Salient Object Detection via 3D Convolutional Neural Networks   \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Qian Chen, Keren Fu, et al.*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://ojs.aaai.org/index.php/AAAI/article/view/16191)/[Code](https://github.com/PPOLYpubki/RD3D) |\n|      ---     |    ---      |    ---       |     ---      |\n|   2021   |  PAMI | MobileSal: Extremely Efficient RGB-D Salient Object Detection  \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Yu-Huan Wu, Yun Liu, Jia-Wang Bian, Yu-Chao Gu, Ming-Ming Cheng*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://mftp.mmcheng.net/Papers/21PAMI_MobileSal.pdf)/[Code](https://github.com/yuhuan-wu/MobileSal)\n|   2021    |   PAMI   | Uncertainty Inspired RGB-D Saliency Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Jing Zhang, Deng-Ping Fan, Yuchao Dai, Saeed Anwaret, et al.*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://ieeexplore.ieee.org/document/9405467)/Code                                                   |\n|   2021    |   PAMI   | Siamese Network for RGB-D Salient Object Detection and Beyond \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Keren Fu, Deng-Ping Fan, et al.*\u003c/sup\u003e\u003c/sub\u003e       | Paper/Code                                                   |\n|   2021    |   IJCV   | CNN-Based RGB-D Salient Object Detection: Learn, Select, and Fuse \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Hao Chen, Youfu Li, et al.*\u003c/sup\u003e\u003c/sub\u003e       | [Paper](https://arxiv.org/pdf/1909.09309.pdf)/Code           |\n|   2021    |   TIP    | Hierarchical Alternate Interaction Network for RGB-D Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Gongyang Li, Haibin Ling, et al.*\u003c/sup\u003e\u003c/sub\u003e         | Paper/Code                                                   |\n|   2021    |   TIP    | Bilateral Attention Network for RGB-D Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Zhao Zhang, Deng-Ping Fan, et al.*\u003c/sup\u003e\u003c/sub\u003e    | [arXiv](https://arxiv.org/abs/2004.14582)/[Code](https://github.com/zzhanghub/bianet) |\n|   2021    |   TIP    | CDNet: Complementary Depth Network for RGB-D Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Wen-Da Jin, Ming-Ming Cheng, et al.*\u003c/sup\u003e\u003c/sub\u003e           | Paper/Code                                                   |\n|   2021    |   TIP    | Data-Level Recombination and Lightweight Fusion Scheme for RGB-D Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Xuehao Wang, et al.*\u003c/sup\u003e\u003c/sub\u003e    | [Paper](https://arxiv.org/abs/2009.05102)/[Code](https://github.com/XueHaoWang-Beijing/DRLF?utm_source=catalyzex.com) |\n|   2021    |   TIP    | RGB-D Salient Object Detection With Ubiquitous Target Awareness \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Yifan Zhao, et al.*\u003c/sup\u003e\u003c/sub\u003e                   | [arXiv](https://arxiv.org/abs/2109.03425)/Code               |\n|   2021    |   TIP    | DPANet: Depth Potentiality-Aware Gated Attention Network for RGB-D Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Zuyao Chen, Runmin Cong, et al.*\u003c/sup\u003e\u003c/sub\u003e           | [Paper](https://arxiv.org/abs/2003.08608)/[Code](https://github.com/JosephChenHub/DPANet) |\n|   2021    |   TIP    | Multi-Interactive Dual-Decoder for RGB-Thermal Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Zhengzheng Tu, et al.*\u003c/sup\u003e\u003c/sub\u003e       | Paper/Code                                                   |\n|   2021    |   TCYB   | ASIF-Net: Attention Steered Interweave Fusion Network for RGB-D Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Chongyi Li, Runmin Cong, et al.*\u003c/sup\u003e\u003c/sub\u003e      | [Paper](https://ieeexplore.ieee.org/document/8998588)/[Code](https://github.com/Li-Chongyi/ASIF-Net) |\n|   2021    |   TNNLS    | IRFR-Net: Interactive Recursive Feature-Reshaping Network for Detecting Salient Objects in RGB-D Images \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Wujie Zhou, Qinling Guo, et al.*\u003c/sup\u003e\u003c/sub\u003e     | [Paper](https://ieeexplore.ieee.org/abstract/document/9519891)/Code |\n|   2021    |   TNNLS    | Rethinking RGB-D Salient Object Detection: Models, Data Sets, and Large-Scale Benchmarks \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Deng-Ping Fan, et al.*\u003c/sup\u003e\u003c/sub\u003e                    | [Paper](https://arxiv.org/abs/1907.06781)/[Code](https://github.com/DengPingFan/D3NetBenchmark) |\n|   2021    |   TMM    | Employing Bilinear Fusion and Saliency Prior Information for RGB-D Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Nianchang Huang, Dingwen Zhang, et al.*\u003c/sup\u003e\u003c/sub\u003e    | Paper/Code                                                   |\n|   2021    |   TMM    | Attentive Cross-Modal Fusion Network for RGB-D Saliency Detection  \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Di Liu, Kao Zhang, Zhenzhong Chen*\u003c/sup\u003e\u003c/sub\u003e  | Paper/Cod                                                    |\n|   2021    |   TMM    | Deep RGB-D Saliency Detection without Depth   \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Yuan-Fang Zhang, et al.*\u003c/sup\u003e\u003c/sub\u003e              | Paper/Code                                                   |\n|   2021    |   TMM    | \u003cspan style=\"white-space:nowrap;\"\u003eCCAFNet: Crossflow and Cross-scale Adaptive Fusion Network for Detecting Salient Objects in RGB-D Images\u0026emsp; \u003c/span\u003e  \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Wujie Zhou, et al.*\u003c/sup\u003e\u003c/sub\u003e     | Paper/Code        |\n\n\n\n\n\n### 2020\n\n| **Year** | **Pub.** | **Title**    | **Links**                                    |\n| :-----: | :------: | :----------------------------------------------------------- |  :----------------------------------------------------------- |\n|   2020    |   ECCV   | RGB-D Salient Object Detection with Cross-Modality Modulation and Selection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Chongyi Li, Runmin Cong, et al.*\u003c/sup\u003e\u003c/sub\u003e             | [Paper](https://arxiv.org/abs/2007.07051)/[Code](https://github.com/Li-Chongyi/cmMS-ECCV20)\u003cbr\u003e[Proj](https://li-chongyi.github.io/Proj_ECCV20) |\n|   2020    |   ECCV   | Progressively Guided Alternate Refinement Network for RGB-D Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Shuhan Chen, Yun Fu*\u003c/sup\u003e\u003c/sub\u003e                   | [Paper](https://arxiv.org/abs/2008.07064)/[Code](https://github.com/ShuhanChen/PGAR_ECCV20?utm_source=catalyzex.com) |\n|   2020    |   ECCV   | BBS-Net: RGB-D Salient Object Detection with a Bifurcated Backbone Strategy Network \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Yingjie Zhai, Deng-Ping Fan, et al.*\u003c/sup\u003e\u003c/sub\u003e            | [Paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123570273.pdf)/[Code](https://github.com/DengPingFan/BBS-Net)\u003cbr\u003e[Extension](https://arxiv.org/pdf/2007.02713.pdf) |\n|   2020    |   ECCV   | Cascade Graph Neural Networks for RGB-D Salient Object Detection  \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Ao Luo, et al.*\u003c/sup\u003e\u003c/sub\u003e   | [Paper](https://arxiv.org/abs/2008.03087)/[Code](https://github.com/LA30/Cas-Gnn?utm_source=catalyzex.com) |\n|   2020    |   ECCV   | Cross-Modal Weighting Network for RGB-D Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Gongyang Li, Haibin Ling, et al.*\u003c/sup\u003e\u003c/sub\u003e            | [Paper](https://arxiv.org/pdf/2007.04901.pdf)/[arXiv](https://arxiv.org/abs/2007.04901)\u003cbr\u003e[Code](https://github.com/MathLee/CMWNet) |\n|   2020    |   ECCV   | Accurate RGB-D Salient Object Detection via Collaborative Learning \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Wei Ji, Huchuan Lu, et al.*\u003c/sup\u003e\u003c/sub\u003e     | [Paper](https://arxiv.org/abs/2007.11782)/[Code](https://github.com/jiwei0921/CoNet) |\n|   2020    |   ECCV   | A Single Stream Network for Robust and Real-time RGB-D Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Xiaoqi Zhao, Lihe Zhang, et al.*\u003c/sup\u003e\u003c/sub\u003e              | [Paper](https://arxiv.org/pdf/2007.06811.pdf)/[Code](https://github.com/Xiaoqi-Zhao-DLUT/DANet-RGBD-Saliency) |\n|   2020    |   ECCV   | Hierarchical Dynamic Filtering Network for RGB-D Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Youwei Pang, Lihe Zhang, Xiaoqi Zhao, Huchuan Lu*\u003c/sup\u003e\u003c/sub\u003e  | [arXiv](https://arxiv.org/abs/2007.06227)/[Code](https://github.com/lartpang/HDFNet) |\n|   2020    |   ECCV   | Asymmetric Two-Stream Architecture for Accurate RGB-D Saliency Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Miao Zhang, Huchuan Lu, et al.*\u003c/sup\u003e\u003c/sub\u003e                | [Paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123730375.pdf)/[Code](https://github.com/OIPLab-DUT/ATSA) |\n|   2020    |    MM    | Is Depth Really Necessary for Salient Object Detection?      \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Jiawei Zhao, Yifan Zhao, Jia Li, Xiaowu Chen*\u003c/sup\u003e\u003c/sub\u003e           | [Paper](https://arxiv.org/pdf/2006.00269.pdf)/[Code](https://github.com/iCVTEAM/DASNet)\u003cbr\u003e[Proj](http://cvteam.net/projects/2020/DASNet/) |\n|   2020    |   CVPR   | Select, Supplement and Focus for RGB-D Saliency Detection    \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Miao Zhang, Yongri Piao, et al.*\u003c/sup\u003e\u003c/sub\u003e                | [Paper](https://openaccess.thecvf.com/content_CVPR_2020/papers/Zhang_Select_Supplement_and_Focus_for_RGB-D_Saliency_Detection_CVPR_2020_paper.pdf)/[Code](https://github.com/OIPLab-DUT/CVPR_SSF-RGBD) |\n|   2020    |   CVPR   | JL-DCF: Joint Learning and Densely-Cooperative Fusion Framework for RGB-D Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Keren Fu, Deng-Ping Fan, Ge-Peng Ji, Qijun Zhao*\u003c/sup\u003e\u003c/sub\u003e         | [Paper](https://openaccess.thecvf.com/content_CVPR_2020/papers/Fu_JL-DCF_Joint_Learning_and_Densely-Cooperative_Fusion_Framework_for_RGB-D_Salient_CVPR_2020_paper.pdf)/[arXiv](https://arxiv.org/abs/2004.08515)/\u003cbr\u003e[PAMI21](https://arxiv.org/pdf/2008.12134.pdf)/[Code](https://github.com/kerenfu/JLDCF/) |\n|   2020    |   CVPR   | A2dele: Adaptive and Attentive Depth Distiller for Efficient RGB-D Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Yongri Piao, Huchuan Lu, et al.*\u003c/sup\u003e\u003c/sub\u003e                     | [Paper](https://openaccess.thecvf.com/content_CVPR_2020/html/Piao_A2dele_Adaptive_and_Attentive_Depth_Distiller_for_Efficient_RGB-D_Salient_CVPR_2020_paper.html)/Code |\n|   2020    |   CVPR   | UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Jing Zhang, Deng-Ping Fan, et al.*\u003c/sup\u003e\u003c/sub\u003e                   | [Paper](https://arxiv.org/abs/2009.03075)/[Code](https://github.com/JingZhang617/UCNet?utm_source=catalyzex.com) |\n|   2020    |   CVPR   | Multi-Scale Interactive Network for Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Youwei Pang, Huchuan Lu, et al.*\u003c/sup\u003e\u003c/sub\u003e       | [Paper](https://openaccess.thecvf.com/content_CVPR_2020/papers/Pang_Multi-Scale_Interactive_Network_for_Salient_Object_Detection_CVPR_2020_paper.pdf)/[Code](https://github.com/lartpang/MINet) |\n|   2020    |   CVPR   | Interactive Two-Stream Decoder for Accurate and Fast Saliency Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*H. Zhou, Xiaohua Xie, Jian-Huang Lai, et al.*\u003c/sup\u003e\u003c/sub\u003e        | [Paper](https://openaccess.thecvf.com/content_CVPR_2020/papers/Zhou_Interactive_Two-Stream_Decoder_for_Accurate_and_Fast_Saliency_Detection_CVPR_2020_paper.pdf)/[Code](https://github.com/moothes/ITSD-pytorch) |\n|   2020    |   CVPR   | Label Decoupling Framework for Salient Object Detection      \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Jun Wei, et al.*\u003c/sup\u003e\u003c/sub\u003e                        | Paper/[Code](https://github.com/weijun88/LDF)                |\n|   2020    |   CVPR   | \u003cspan style=\"white-space:nowrap;\"\u003eLearning Selective Self-Mutual Attention for RGB-D Saliency Detection\u0026emsp;\u003c/span\u003e   \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Nian Liu, Ni Zhang, et al.*\u003c/sup\u003e\u003c/sub\u003e    | Paper/[Code](https://github.com/nnizhang/SMAC?utm_source=catalyzex.com)\u003cbr\u003e[Ext](https://arxiv.org/abs/2010.05537) |\n|      ---     |    ---      |    ---       |     ---      |\n|   2020    |   TIP    | RGBD Salient Object Detection via Disentangled Cross-Modal Fusion \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Hao Chen, et al.*\u003c/sup\u003e\u003c/sub\u003e      | Paper/Code                                                   |\n|   2020    |   TIP    | RGBD Salient Object Detection via Deep Fusion           \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Liangqiong Qu, et al.*\u003c/sup\u003e\u003c/sub\u003e  | [Paper](http://www.shengfenghe.com/qfy-content/uploads/2019/12/4853ab33ac9a11e019f165388e57acf1.pdf)/Code |\n|   2020    |   TIP    | Boundary-Aware RGBD Salient Object Detection With Cross-Modal Feature Sampling  \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Yuzhen Niu, et al.*\u003c/sup\u003e\u003c/sub\u003e              | Paper/Code                                                   |\n|   2020    |   TIP    | ICNet: Information Conversion Network for RGB-D Based Salient Object Detection  \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Gongyang Li, Zhi Liu, Haibin Ling*\u003c/sup\u003e\u003c/sub\u003e           | Paper/Code                                                   |\n|   2020    |   TIP    | Improved Saliency Detection in RGB-D Images Using Two-Phase Depth Estimation and Selective Deep Fusion \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Chenglizhao Chen, et al.*\u003c/sup\u003e\u003c/sub\u003e                     | Paper/Code                                                   |\n|   2020    |   TCYB   | Discriminative Cross-Modal Transfer Learning and Densely Cross-Level Feedback Fusion for RGB-D Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Hao Chen, Youfu Li, Dan Su*\u003c/sup\u003e\u003c/sub\u003e                   | Paper/Code                                                   |\n|   2020    |   TCYB   | Going From RGB to RGBD Saliency: A Depth-Guided Transformation Model \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Runmin Cong, et al.*\u003c/sup\u003e\u003c/sub\u003e  | Paper/Code                                                   |\n|   2020    |   TMM    | cmSalGAN: RGB-D Salient Object Detection With Cross-View Generative Adversarial Networks \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Bo Jiang, et al.*\u003c/sup\u003e\u003c/sub\u003e                    | [Paper](https://arxiv.org/pdf/1912.10280.pdf)/[Code](https://github.com/wangxiao5791509/cmSalGAN_PyTorch)\u003cbr\u003e[Proj](https://sites.google.com/view/cmsalgan/) |\n|   2020    |   TMM    | \u003cspan style=\"white-space:nowrap;\"\u003eJoint Cross-Modal and Unimodal Features for RGB-D Salient Object Detection \u0026emsp;\u003c/span\u003e   \u003cbr\u003e \u003csub\u003e\u003csup\u003e*N. Huang, Yi Liu, Qiang Zhang, Jungong Han*\u003c/sup\u003e\u003c/sub\u003e    | Paper/Code \n\n\n\n\n### 2019 \n\n| **Year** | **Pub.** | **Title**         | **Links**                               |\n| :-----: | :------: | :----------------------------------------------------------- | :----------------------------------------------------------- |\n|   2019    |   ICCV   | EGNet: Edge Guidance Network for Salient Object Detection    \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Jia-Xing Zhao, Ming-Ming Cheng, et al.*\u003c/sup\u003e\u003c/sub\u003e             | [Paper](https://openaccess.thecvf.com/content_ICCV_2019/papers/Zhao_EGNet_Edge_Guidance_Network_for_Salient_Object_Detection_ICCV_2019_paper.pdf)/[Code](https://github.com/JXingZhao/EGNet) |\n|   2019    |   ICCV   | Depth-induced Multi-scale Recurrent Attention Network for Saliency Detection   \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Wei Ji, Jingjing Li, Miao Zhang, Huchuan Lu*\u003c/sup\u003e\u003c/sub\u003e                | [Paper](https://openaccess.thecvf.com/content_ICCV_2019/papers/Piao_Depth-Induced_Multi-Scale_Recurrent_Attention_Network_for_Saliency_Detection_ICCV_2019_paper.pdf)/[Code](https://github.com/jiwei0921/DMRA)\u003cbr\u003e[Ext-22](https://ieeexplore.ieee.org/document/9729103) |\n|   2019    |   CVPR   | \u003cspan style=\"white-space:nowrap;\"\u003eContrast Prior and Fluid Pyramid Integration for RGBD Salient Object Detection\u0026emsp;\u003c/span\u003e   \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Jia-Xing Zhao, Ming-Ming Cheng, et al.*\u003c/sup\u003e\u003c/sub\u003e           | [Paper](http://mftp.mmcheng.net/Papers/19cvprRrbdSOD.pdf)/[Code](https://github.com/JXingZhao/ContrastPrior)\u003cbr\u003e[Proj](https://mmcheng.net/rgbdsalpyr/) |\n|   2019    |   CVPR   | BASNet: Boundary-Aware Salient Object Detection  \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Xuebin Qin, Zichen Zhang, Chenyang Huang, Chao Gao, et al.*\u003c/sup\u003e\u003c/sub\u003e         | [Paper](https://openaccess.thecvf.com/content_CVPR_2019/papers/Qin_BASNet_Boundary-Aware_Salient_Object_Detection_CVPR_2019_paper.pdf)/[Code](https://github.com/xuebinqin/BASNet)\u003cbr\u003e[Ext](https://arxiv.org/abs/2101.04704)        |\n|      ---     |    ---      |    ---       |     ---      |\n|   2019    |   TIP    | Three-Stream Attention-Aware Network for RGB-D Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Hao Chen, Youfu Li*\u003c/sup\u003e\u003c/sub\u003e   | [Paper](https://ieeexplore.ieee.org/document/8603756)/Code   |\n|   2019    |   TIP    | RGB-'D' Saliency Detection With Pseudo Depth      \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Xiaolin Xiao, Yicong Zhou, Yue-Jiao Gong*\u003c/sup\u003e\u003c/sub\u003e                 |   [Paper](https://ieeexplore.ieee.org/document/8540072)/[Code](https://github.com/shellyXXL/RGB-D-saliency-detection-with-pseudo-depth)         |\n\n\n\n\n### 2018\n\n| **Year** | **Pub.** | **Title**                                                   | **Links** |\n| :-----: | :------: | :----------------------------------------------------------- | :-------- |\n|   2018    |   CVPR   | Progressively Complementarity-Aware Fusion Network for RGB-D Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Hao Chen, Youfu Li*\u003c/sup\u003e\u003c/sub\u003e   |     Paper/Code      |\n|   2018    |   CVPR   | \u003cspan style=\"white-space:nowrap;\"\u003ePiCANet: Learning Pixel-wise Contextual Attention for Saliency Detection \u0026emsp;\u003c/span\u003e              |     Paper/Code      |\n|   2018    |   TCYB   | CNNs-Based RGB-D Saliency Detection via Cross-View Transfer and Multiview Fusion  \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Junwei Han, et al.*\u003c/sup\u003e\u003c/sub\u003e        |   Paper/Code        |\n\n\n\n\n### 2017\n\n| **Year** | **Pub.** | **Title**                                                   | **Links** |\n| :-----: | :------: | :----------------------------------------------------------- | :-------- |\n|   2017    |   CVPR   | Instance-Level Salient Object Segmentation       |   Paper/Code      |\n|   2017    |   TIP    | Depth-Aware Salient Object Detection and Segmentation via Multiscale Discriminative Saliency Fusion and Bootstrap Learning  \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Hangke Song, et al.*\u003c/sup\u003e\u003c/sub\u003e      |      Paper/Code     |\n|   2017    |   TIP    | \u003cspan style=\"white-space:nowrap;\"\u003eEdge Preserving and Multi-Scale Contextual Neural Network for Salient Object Detection \u0026emsp;\u003c/span\u003e   \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Xiang Wang, Huimin Ma, Xiaozhi Chen, Shaodi You*\u003c/sup\u003e\u003c/sub\u003e   |  Paper/Code  |\n\n\n\n### Beyond\n\n| **Year** | **Pub.** | **Title**                                                    | **Links**      |\n| :------: | :------: | :----------------------------------------------------------- |  :-------|\n| 2021 | arXiv02 | CPP-Net: Context-aware Polygon Proposal Network for Nucleus Segmentation \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Shengcong Chen, Changxing Ding, Minfeng Liu, Dacheng Tao*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://arxiv.org/abs/2102.06867)/Code |\n|   2019   | NeurIPS  | \u003cspan style=\"white-space:nowrap;\"\u003eOne-Shot Object Detection with Co-Attention and Co-Excitation \u0026emsp;\u003c/span\u003e   \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Ting-I Hsieh, et al.*\u003c/sup\u003e\u003c/sub\u003e                                         | [Paper](https://papers.nips.cc/paper/2019/file/92af93f73faf3cefc129b6bc55a748a9-Paper.pdf)/[Code](https://github.com/timy90022/One-Shot-Object-Detection) |\n|   2020   | NeurIPS  | Deep Multimodal Fusion by Channel Exchanging                 \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Yikai Wang, et al.*\u003c/sup\u003e\u003c/sub\u003e      | [Paper](https://papers.nips.cc/paper/2020/file/339a18def9898dd60a634b2ad8fbbd58-Paper.pdf)/[Code](https://github.com/yikaiw/CEN) |\n|   2021   |    MM    | Occlusion-aware Bi-directional Guided Network for Light Field Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Dong Jing, Runmin Cong, et al.*\u003c/sup\u003e\u003c/sub\u003e                               | Paper/Code                  |\n|   2021   |   ICCV   | **Contrastive Multimodal Fusion with TupleInfoNCE**          \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Yunze Liu, Li Yi, et al.*\u003c/sup\u003e\u003c/sub\u003e                                     | [Paper](https://arxiv.org/pdf/2107.02575.pdf)/Code           |\n|   2019   |   ICCV   | RGB-Infrared Cross-Modality Person Re-Identification via Joint Pixel and Feature Alignment \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Guan'an Wang, et al.*\u003c/sup\u003e\u003c/sub\u003e              | Paper/[Code](https://github.com/wangguanan/AlignGAN)         |\n| 2021 | CVPR | Look Closer to Segment Better: Boundary Patch Refinement for Instance Segmentation \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Chufeng Tang, Xiaolin Hu, et al.*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://openaccess.thecvf.com/content/CVPR2021/html/Tang_Look_Closer_To_Segment_Better_Boundary_Patch_Refinement_for_Instance_CVPR_2021_paper.html)/[Code](https://github.com/tinyalpha/BPR) |\n| 2021 | CVPR | Boundary IoU: Improving Object-Centric Image Segmentation Evaluation \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Bowen Cheng, Ross Girshick, Piotr Dollár, et al.*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://openaccess.thecvf.com/content/CVPR2021/html/Cheng_Boundary_IoU_Improving_Object-Centric_Image_Segmentation_Evaluation_CVPR_2021_paper.html)/[Code](https://bowenc0221.github.io/boundary-iou/) |\n| 2021 | AAAI | Active Boundary Loss for Semantic Segmentation  \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Chi Wang, Yunke Zhang, Miaomiao Cui, Peiran Ren, et al.*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://www.aaai.org/AAAI22Papers/AAAI-2277.WangC.pdf)/Code |\n|      ---     |    ---      |    ---       |     ---      |\n|   2021   |   TCYB   | PANet: Patch-Aware Network for Light Field Salient Object Detection  \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Yongri Piao, Huchuan Lu, et al.*\u003c/sup\u003e\u003c/sub\u003e                              | Paper/Code                                                   |\n| 2021 | TIP | Progressive Self-Guided Loss for Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Sheng Yang, Weisi Lin, et al.*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://arxiv.org/abs/2101.02412)/Code |\n|   2020   |   TIP    | RGB-T Salient Object Detection via Fusing Multi-Level CNN Features \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Qiang Zhang, Dingwen Zhang, et al.*\u003c/sup\u003e\u003c/sub\u003e                           | Paper/Code                                                   |\n|   2020   |   TIP    | LFNet: Light Field Fusion Network for Salient Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Miao Zhang, Huchuan Lu, et al.*\u003c/sup\u003e\u003c/sub\u003e                               | Paper/Code                                                   |\n|   2019   |   TIP    | Cross-Modal Attentional Context Learning for RGB-D Object Detection \u003cbr\u003e \u003csub\u003e\u003csup\u003e*G. Li, Liang Lin, et al.*\u003c/sup\u003e\u003c/sub\u003e | Paper/Code                                                   |\n|   2019   |   TMM    | RGB-T Image Saliency Detection via Collaborative Graph Learning   \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Zhengzheng Tu, et al.*\u003c/sup\u003e\u003c/sub\u003e                                        | Paper/Code                                                   |\n\n\n\n## RGB-T SOD\n\n| **Year** | **Pub.** | **Title**                                                    | **Links**      |\n| :------: | :------: | :----------------------------------------------------------- |  :-------|\n| 2024 |   PR  | Frequency-aware feature aggregation network with dual-task consistency for RGB-T salient object detection     \u003cbr\u003e\u003csub\u003e\u003csup\u003e*Heng Zhou, Chunna Tian, Zhenxi Zhang, Chengyang Li, Yongqiang Xie, Zhongbo Li*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://www.sciencedirect.com/science/article/abs/pii/S0031320323007409?dgcid=raven_sd_via_email)/Code\n| 2023 | TCSVT | Cross-Modality Double Bidirectional Interaction and Fusion Network for RGB-T Salient Object Detection  \u003cbr\u003e\u003csub\u003e\u003csup\u003e*Zhengxuan Xie; Feng Shao; Gang Chen; Hangwei Chen; Qiuping Jiang; Xiangchao Meng; Yo-Sung Ho*\u003c/sup\u003e\u003c/sub\u003e | Paper/Code\n| 2023 | TCSVT | Multiple Graph Affinity Interactive Network and a Variable Illumination Dataset for RGBT Image Salient Object Detection  \u003cbr\u003e\u003csub\u003e\u003csup\u003e*Kechen Song; Liming Huang; Aojun Gong; Yunhui Yan*\u003c/sup\u003e\u003c/sub\u003e | Paper/Code\n| 2022 | KBS | Asymmetric cross-modal activation network for RGB-T salient object detection  \u003cbr\u003e\u003csub\u003e\u003csup\u003e*Chang Xu, Qingwu Li, Qingkai Zhou, Xiongbiao Jiang, Dabing Yu, Yaqin Zhou*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://www.sciencedirect.com/science/article/abs/pii/S0950705122011406)/[Code](https://github.com/xanxuso/ACMANet)\n| 2022 | TMM | Does Thermal really always matter for RGB-T salient object detection \u003cbr\u003e\u003csub\u003e\u003csup\u003e*Runmin Cong, Kepu Zhang, Chen Zhang, Feng Zheng, Yao Zhao, Qingming Huang, Sam Kwong*\u003c/sup\u003e\u003c/sub\u003e  | [Paper](https://arxiv.org/pdf/2210.04266.pdf)/[Code](https://rmcong.github.io/proj_TNet.html)\n| 2022 | TCSVT | Cross-Collaborative Fusion-Encoder Network for Robust RGB-Thermal Salient Object Detection  \u003cbr\u003e\u003csub\u003e\u003csup\u003e*Guibiao Liao, Wei Gao, Ge Li, Junle Wang, Sam Kwong*\u003c/sup\u003e\u003c/sub\u003e  | [Paper](https://ieeexplore.ieee.org/document/9801871?source=tocalert\u0026dld=Z21haWwuY29t)/[Code](https://git.openi.org.cn/OpenVision/CCFENet)\n| 2022 | TIM | Real-time One-stream Semantic-guided Refinement Network for RGB-Thermal Salient Object Detection  \u003cbr\u003e\u003csub\u003e\u003csup\u003e*Fushuo Huo, Xuegui Zhu, Qian Zhang, Ziming Liu, Wenchao Yu*\u003c/sup\u003e\u003c/sub\u003e  | [Paper](https://ieeexplore.ieee.org/abstract/document/9803225)/[Code](https://github.com/huofushuo/OSRNet)\n| 2022 | TIP | Weakly Alignment-free RGBT Salient Object Detection with Deep Correlation Network   \u003cbr\u003e\u003csub\u003e\u003csup\u003e*Zhengzheng Tu, Zhun Li, Chenglong Li, Jin Tang*\u003c/sup\u003e\u003c/sub\u003e  | [Paper](https://ieeexplore.ieee.org/abstract/document/9779787)/[Code](https://github.com/lz118/Deep-Correlation-Network)\n\n\n\n\n## V-D-T SOD\n\n| **Year** | **Pub.** | **Title** |  **Links**                                       |\n| :-----: | :------: | :----------------------------------------------------------- |   :----------------------------------------------------------- |\n| 2024  | TCSVT| Dynamic Weighted Fusion and Progressive Refinement Network for Visible-Depth-Thermal Salient Object Detection   \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Yi Luo; Feng Shao; Baoyang Mu; Hangwei Chen; Zhuo Li; Qiuping Jiang*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://ieeexplore.ieee.org/document/10556617)/Code\n| 2024  |  TIP  |\tQuality-Aware Selective Fusion Network for V-D-T Salient Object Detection   \u003cbr\u003e \u003csub\u003e\u003csup\u003e*Liuxin Bao, Xiaofei Zhou, Xiankai Lu, Yaoqi Sun, Haibing Yin, Zhenghui Hu, Jiyong Zhang, Chenggang Yan*\u003c/sup\u003e\u003c/sub\u003e | [Paper](https://arxiv.org/abs/2405.07655)/[Code](https://github.com/Lx-Bao/QSFNet) \n\n\n\n## Image SOD\n\n#### Preprint\n\n| **Year.** | **Title**                                                    | **Author**                                                   | **Links**                                                    |\n| :------: | :----------------------------------------------------------- | :----------------------------------------------------------- | :----------------------------------------------------------- |\n2022 | DFTR: Depth-supervised Fusion Transformer for Salient Object Detection | Heqin Zhu, et al. | [Paper](https://arxiv.org/abs/2203.06429)/Code\n\n\n\n#### 2024\n\n| **Pub.** | **Title**                                                    | **Author**                                                   | **Links**                                                    |\n| :------: | :----------------------------------------------------------- | :----------------------------------------------------------- | :----------------------------------------------------------- |\nICML | Size-invariance Matters: Rethinking Metrics and Losses for Imbalanced Multi-object Salient Object Detection | Feiran Li, Qianqian Xu, et al. | [Paper](https://arxiv.org/abs/2405.09782)/[Code](https://github.com/Ferry-Li/SI-SOD)\n\n\n#### 2022\n\n| **Pub.** | **Title**                                                    | **Author**                                                   | **Links**                                                    |\n| :------: | :----------------------------------------------------------- | :----------------------------------------------------------- | :----------------------------------------------------------- |\nCVPR | Pyramid Grafting Network for One-Stage High Resolution Saliency Detection | Chenxi Xie, Jia Li, et al. | [Paper](https://arxiv.org/abs/2204.05041)/[Code](https://github.com/iCVTEAM/PGNet)\nAAAI | Unsupervised Domain Adaptive Salient Object Detection Through Uncertainty-Aware Pseudo-Label Learning | Pengxiang Yan, Liang Lin, et al. | [Paper](https://arxiv.org/abs/2202.13170)/[Code](https://github.com/Kinpzz/UDASOD-UPL)\nAAAI | Weakly-Supervised Salient Object Detection Using Point Supervison | Shuyong Gao, Wei Zhang, et al. | [Paper](https://arxiv.org/pdf/2203.11652.pdf)/[Code](https://github.com/shuyonggao/PSOD)\n\n\n\n#### 2021 \n\n| **Pub.** | **Title**                                                    | **Author**                                                   | **Links**                                                    |\n| :------: | :----------------------------------------------------------- | :----------------------------------------------------------- | :----------------------------------------------------------- |\n| NeurIPS | Learning Generative Vision Transformer with Energy-Based Latent Space for Saliency Prediction | Jing Zhang, Jianwen Xie, et al. | [Paper](https://papers.nips.cc/paper/2021/file/8289889263db4a40463e3f358bb7c7a1-Paper.pdf)/Code\n|  arXiv08   | Unifying Global-Local Representations in Salient Object Detection with Transformer  | Sucheng Ren, Qiang Wen, et al. | [Paper](https://arxiv.org/abs/2108.02759)/Code\n|  arXiv01   | Boundary-Aware Segmentation Network for Mobile and Web Applications | Xuebin Qin, Deng-Ping Fan, et al.                            | [Paper](https://arxiv.org/abs/2101.04704)/[Code](https://github.com/xuebinqin/BASNet) |\n|   PAMI   | Part-Object Relational Visual Saliency                       | Yi Liu, Dingwen Zhang, et al.                                |                                                              |\n|   PAMI   | Saliency Prediction in the Deep Learning Era: Successes and Limitations | Ali Borji                                                    |                                                              |\n|   PAMI   | Salient Object Detection in the Deep Learning Era: An In-depth Survey | Wenguan Wang, et al.                                         |                                                              |\n|   PAMI   | Revisiting Video Saliency Prediction in the Deep Learning Era | Wenguan Wang, et al.                                         |                                                              |\n|   PAMI   | Relative Saliency and Ranking: Models, Metrics, Data and Benchmarks | Mahmoud Kalash, Md Amirul Islam, et al.                      |                                                              |\n|   PAMI   | Instance-Level Relative Saliency Ranking with Graph Reasoning | Nian Liu, et al.                                             |                                                              |\n|   PAMI   | Learning Saliency From Single Noisy Labelling: A Robust Model Fitting Perspective | Jing Zhang, Yuchao Dai, et al.                               |                                                              |\n|   PAMI   | Deep Cognitive Gate: Resembling Human Cognition for Saliency Detection | Ke Yan, et al.                                               |                                                              |\n|   PAMI   | A Highly Efficient Model to Study the Semantics of Salient Object Detection | Ming-Ming Cheng, et al.                                      |                                                              |\n|   PAMI   | Learning to Detect Salient Object with Multi-source Weak Supervision | Hongshuang Zhang, Huchuan Lu, et al.                         |                                                              |\n|   IJCV   | Saliency Detection Inspired by Topological Perception Theory | Peng Peng, Yong-Jie Li, etc                                  | [Paper](https://link.springer.com/article/10.1007/s11263-021-01478-4)/Code |\n|   TIP    | Rethinking Image Salient Object Detection: Object-Level Semantic Saliency Reranking First, Pixelwise Saliency Refinement Later | Guangxiao Ma, et al.                                         |                                                              |\n|   TIP    | Contour-Aware Loss: Boundary-Aware Learning for Salient Object Segmentation | Zixuan Chen, Jianhuang Lai, et al.                           |                                                              |\n|   TIP    | Depth-Quality-Aware Salient Object Detection                 | Chenglizhao Chen, et al.                                     |                                                              |\n|   TIP    | Dense Attention Fluid Network for Salient Object Detection in Optical Remote Sensing Images | Qijian Zhang, Runmin Cong, et al.                            |                                                              |\n|   TIP    | SCG: Saliency and Contour Guided Salient Instance Segmentation | Nian Liu, et al.                                             |                                                              |\n|   TIP    | Hierarchical and Interactive Refinement Network for Edge-Preserving Salient Object Detection | Sanping Zhou, et al.                                         |                                                              |\n|   TIP    | Salient Object Detection With Purificatory Mechanism and Structural Similarity Loss | Jia Li, et al.                                               |                                                              |\n|   TIP    | Hierarchical Edge Refinement Network for Saliency Detection  | D. Song, Yongsheng Dong, Xuelong Li                          |                                                              |\n|   ICCV   | Scene Context-Aware Salient Object Detection                 | Avishek Siris, Jianbo Jiao, et al.                           | Paper/Code                                                   |\n|   ICML   | DANCE: Enhancing saliency maps using decoys                  | Yang Lu, Willian Stafford Noble, et al.                      | Paper/[Code](https://bitbucket.org/noblelab/dance/src/master/) |\n|   AAAI   | Pyramidal Feature Shrinking for Salient Object Detection     | Mingcan Ma, Changqun Xia, Jia Li                             |                                                              |\n|   AAAI   | \u003cspan style=\"white-space:nowrap;\"\u003eLocate Globally, Segment Locally: A Progressive Architecture With Knowledge Review Network for Salient Object Detection\u0026emsp;\u003c/span\u003e | \u003cspan style=\"white-space:nowrap;\"\u003eBinwei Xu, et al.\u0026emsp;\u0026emsp;\u0026emsp;\u0026emsp;\u003c/span\u003e | [Paper](https://ojs.aaai.org/index.php/AAAI/article/view/16408)/Code |\n\n#### 2020 \n\n| **Pub.** | **Title**                                                    | **Author**                                                   | **Links**                                                    |\n| :------- | :----------------------------------------------------------- | :----------------------------------------------------------- | :----------------------------------------------------------- |\n| PAMI     | Inferring Salient Objects from Human Fixations               | Wenguan Wang, Jianbing Shen, et al.                          | Paper/[Code](https://github.com/wenguanwang/ASNet)           |\n| PAMI     | Synthesizing Supervision for Learning Deep Saliency Network without Human Annotation | Dingwen Zhang, et al.                                        |                                                              |\n| TIP      | PiCANet: Pixel-Wise Contextual Attention Learning for Accurate Saliency Detection | Nian Liu, Junwei Han, Ming-Hsuan Yang                        |                                                              |\n| TIP      | Reverse Attention-Based Residual Network for Salient Object Detection | Shuhan Chen, Huchuan Lu, et al.                              |                                                              |\n| TIP      | Boundary-Aware RGBD Salient Object Detection With Cross-Modal Feature Sampling | Yuzhen Liu, et al.                                           |                                                              |\n| TCYB     | Complementarity-Aware Attention Network for Salient Object Detection | Junxia Li, Qingshan Liu, et al.                              |                                                              |\n| NeurIPS  | Few-Cost Salient Object Detection with Adversarial-Paced Learning | Dingwen Zhang, Haibin Tian, et al.                           | Paper/[Code](https://github.com/hb-stone/FC-SOD)             |\n| ECCV     | Suppress and Balance: A Simple Gated Network for Salient Object | Xiaoqi Zhao, Huchuan Lu, et al.                              | [Paper](https://arxiv.org/pdf/2007.08074.pdf)/[Code](https://github.com/Xiaoqi-Zhao-DLUT/GateNet-RGB-Saliency) |\n| CVPR     | Inferring Attention Shift Ranks of Objects for Image Saliency | Avishek Siris, Jianbo Jiao, et al.                           | [Paper](https://jianbojiao.com/pdfs/CVPR20.pdf)/[Code](https://github.com/SirisAvishek/Attention_Shift_Ranks) |\n| CVPR     | Weakly-Supervised Salient Object Detection via Scribble Annotations | Jing Zhang, Yuchao Dai, et al.                               | [Paper](https://openaccess.thecvf.com/content_CVPR_2020/html/Zhang_Weakly-Supervised_Salient_Object_Detection_via_Scribble_Annotations_CVPR_2020_paper.html)/[Code](https://github.com/JingZhang617/Scribble_Saliency) |\n| AAAI     | Learning Deep Relations to Promote Saliency Detection        | Changrui Chen, et al.                                        |                                                              |\n| AAAI     | Global Context-Aware Progressive Aggregation Network for Salient Object Detection | \u003cspan style=\"white-space:nowrap;\"\u003eZ. Chen, Runmin Cong, et al.\u0026emsp;\u003c/span\u003e | [Paper](https://ojs.aaai.org//index.php/AAAI/article/view/6633)/Code |\n| AAAI     | \u003cspan style=\"white-space:nowrap;\"\u003eF³Net: Fusion, Feedback and Focus for Salient Object Detection \u0026emsp;\u003c/span\u003e | Jun Wei, et al.                                              | [Paper](https://ojs.aaai.org//index.php/AAAI/article/view/6916)/[Code](https://github.com/weijun88/F3Net) |\n\n#### 2019 \n\n| **Pub.** | **Title**                                                    | **Author**                                                   | **Links**                                                    |\n| :------: | :----------------------------------------------------------- | :----------------------------------------------------------- | :----------------------------------------------------------- |\n|   PAMI   | Salient Object Detection with Recurrent Fully Convolutional Networks | L. Wang, Huchuan Lu, et al.                                  |                                                              |\n|   PAMI   | Deeply Supervised Salient Object Detection with Short Connections | Qibin Hou, et al.                                            |                                                              |\n|   PAMI   | What Do Different Evaluation Metrics Tell Us About Saliency Models? | Zoya Bylinskii, et al.                                       |                                                              |\n|   PAMI   | Personalized Saliency and Its Prediction                     | Y. Xu, Jingyi Yu, et al.                                     |                                                              |\n|   IJCV   | Unsupervised Learning of Foreground Object Segmentation      | Ioana Croitoru, Simion-Vlad Bogolin, et al.                  |                                                              |\n|   TIP    | Focal Boundary Guided Salient Object Detection               | Yupei Wang, et al.                                           |                                                              |\n|   ICCV   | Employing Deep Part-Object Relationships for Salient Object Detection |                                                              |                                                              |\n|   ICCV   | Selectivity or Invariance: Boundary-Aware Salient Object Detection | Jinming Su, Jia Li, et al.                                   |                                                              |\n|   ICCV   | Stacked Cross Refinement Network for Edge-Aware Salient Object Detection |                                                              |                                                              |\n|   CVPR   | Salient Object Detection With Pyramid Attention and Salient Edges | Wenguan Wang, Jianbing Shen, et al.                          | [Paper](https://openaccess.thecvf.com/content_CVPR_2019/papers/Wang_Salient_Object_Detection_With_Pyramid_Attention_and_Salient_Edges_CVPR_2019_paper.pdf)/Code |\n|   CVPR   | Attentive Feedback Network for Boundary-Aware Salient Object Detection |                                                              |                                                              |\n|   CVPR   | Pyramid Feature Attention Network for Saliency Detection     |                                                              |                                                              |\n|   AAAI   | Image Saliency Prediction in Transformed Domain: A Deep Complex Neural Network Method | Lai Jiang, et al.                                            |                                                              |\n|   AAAI   | \u003cspan style=\"white-space:nowrap;\"\u003eSuperVAE: Superpixelwise Variational Autoencoder for Salient Object Detection\u0026emsp;\u003c/span\u003e | \u003cspan style=\"white-space:nowrap;\"\u003eBo Li, Z. Sun, Yuqi Guo\u0026emsp;\u003c/span\u003e | [Paper](https://ojs.aaai.org//index.php/AAAI/article/view/4876)/Code |\n\n#### 2018 \n\n| **Pub.** | **Title**                                                    | **Author**                                                   | **Links**                                                    |\n| :------: | :----------------------------------------------------------- | :----------------------------------------------------------- | :----------------------------------------------------------- |\n|   ECCV   | Reverse Attention for Salient Object Detection               |                                                              |                                                              |\n|   ECCV   | Contour Knowledge Transfer for Salient Object Detection      |                                                              |                                                              |\n|   ECCV   | Learning to Zoom: a Saliency-Based Sampling Layer for Neural Networks |                                                              |                                                              |\n|   AAAI   | Lateral Inhibition-Inspired Convolutional Neural Network for Visual Attention and Saliency Detection | Chunshui Cao, Liang Wang, et al.                             |                                                              |\n|   AAAI   | \u003cspan style=\"white-space:nowrap;\"\u003eRecurrently Aggregating Deep Features for Salient Object Detection\u0026emsp;\u003c/span\u003e | \u003cspan style=\"white-space:nowrap;\"\u003eXiaowei Hu, et al.\u0026emsp;\u003c/span\u003e | [Paper](https://aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16775)/Code |\n\n#### 2017 \n\n| **Pub.** | **Title**                                                    | **Author**                                                   | **Links** |\n| :------: | :----------------------------------------------------------- | :----------------------------------------------------------- | :-------- |\n|   PAMI   | Ranking Saliency                                             | Lihe Zhang, Ming-Hsuan Yang, et al.                          |           |\n|   IJCV   | Attentive Systems: A Survey                                  | Tam V. Nguyen, Qi Zhao, Shuicheng Yan                        |           |\n|   IJCV   | \u003cspan style=\"white-space:nowrap;\"\u003eSalient Object Detection: A Discriminative Regional Feature Integration Approach\u0026emsp;\u003c/span\u003e | \u003cspan style=\"white-space:nowrap;\"\u003eJingdong Wang, et al.\u0026emsp;\u003c/span\u003e |           |\n\n\n\n\n## Appendix\n\n- [SOD CNNs-based Read List](https://github.com/jiwei0921/SOD-CNNs-based-code-summary-)\n- [RGB-D SOD Survey](https://github.com/taozh2017/RGBD-SODsurvey)\n- [RGB-T Salient Object Detection and Semantic segmentation](https://github.com/zyrant/Summary-of-RGB-T-Salient-Object-Detection-and-Semantic-segmentation)\n\n","projects_url":"https://awesome.ecosyste.ms/api/v1/lists/visionxiang%2Fawesome-salient-object-detection/projects"}