{"id":20599662,"url":"https://github.com/adamdad/awesome-metrics-learning","last_synced_at":"2026-03-06T23:32:54.994Z","repository":{"id":135591685,"uuid":"274038833","full_name":"Adamdad/Awesome-metrics-learning","owner":"Adamdad","description":null,"archived":false,"fork":false,"pushed_at":"2020-06-22T05:14:27.000Z","size":11,"stargazers_count":14,"open_issues_count":0,"forks_count":3,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-11-12T04:01:53.192Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"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/Adamdad.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}},"created_at":"2020-06-22T04:23:10.000Z","updated_at":"2025-05-22T03:40:04.000Z","dependencies_parsed_at":"2024-04-07T08:15:54.030Z","dependency_job_id":null,"html_url":"https://github.com/Adamdad/Awesome-metrics-learning","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Adamdad/Awesome-metrics-learning","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Adamdad%2FAwesome-metrics-learning","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Adamdad%2FAwesome-metrics-learning/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Adamdad%2FAwesome-metrics-learning/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Adamdad%2FAwesome-metrics-learning/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Adamdad","download_url":"https://codeload.github.com/Adamdad/Awesome-metrics-learning/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Adamdad%2FAwesome-metrics-learning/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":30203362,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-03-06T19:07:06.838Z","status":"ssl_error","status_checked_at":"2026-03-06T18:57:34.882Z","response_time":250,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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"}},"keywords":[],"created_at":"2024-11-16T08:33:42.538Z","updated_at":"2026-03-06T23:32:54.976Z","avatar_url":"https://github.com/Adamdad.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# Awesome-metrics-learning\nA collection of all metric learning paper about loss functions from 2016-today in CVPR, ECCV, ICCV, NIPS, ICML, ICLR and BMVC.\n\n### Older\n- [Neighbourhood Components Analysis](https://www.cs.toronto.edu/~hinton/absps/nca.pdf) (NIPS '05)\n- [Distance Metric Learning for Large Margin\nNearest Neighbor Classification](https://papers.nips.cc/paper/2795-distance-metric-learning-for-large-margin-nearest-neighbor-classification.pdf) (NIPS '06)\n- [Dimensionality Reduction by Learning an Invariant Mapping](http://yann.lecun.com/exdb/publis/pdf/hadsell-chopra-lecun-06.pdf) (CVPR '06)\n- [FaceNet: A Unified Embedding for Face Recognition and Clustering](https://arxiv.org/abs/1503.03832) (CVPR '15)\n\n### 2016\n- [Large-Margin Softmax Loss for Convolutional Neural Networks](https://arxiv.org/abs/1612.02295) (ICML '16)\n- [Improved Deep Metric Learning with Multi-class N-pair Loss Objective](https://papers.nips.cc/paper/6200-improved-deep-metric-learning-with-multi-class-n-pair-loss-objective) (NIPS '16)\n- [Deep Metric Learning via Lifted Structured Feature Embedding](https://arxiv.org/abs/1511.06452) (CVPR '16)\n\n### 2017 \n- [SphereFace: Deep Hypersphere Embedding for Face Recognition](https://arxiv.org/abs/1704.08063)(CVPR '17)\n- [Deep Metric Learning with Angular Loss](https://arxiv.org/abs/1708.01682) (ICCV '17)\n- [No Fuss Distance Metric Learning using Proxies](https://arxiv.org/abs/1703.07464) (ICCV '17)\n- [Sampling Matters in Deep Embedding Learning](https://arxiv.org/abs/1706.07567) （ICCV '17）\n\n### 2018\n- [CosFace: Large Margin Cosine Loss for Deep Face Recognition](https://arxiv.org/abs/1801.09414) (CVPR '18)\n- [Classification is a Strong Baseline for Deep Metric Learning](https://arxiv.org/abs/1811.12649) (BMVC '18)\n- [Additive Margin Softmax for Face Verification](https://pdfs.semanticscholar.org/93af/36da08bf99e68c9b0d36e141ed8154455ac2.pdf) (ICLRW '18)\n\n### 2019\n- [ArcFace: Additive Angular Margin Loss for Deep Face Recognition](https://arxiv.org/abs/1801.07698) (CVPR '19)\n- [Deep Metric Learning to Rank](http://cs-people.bu.edu/hekun/papers/CVPR2019FastAP.pdf) (CVPR '19)\n- [Multi-Similarity Loss with General Pair Weighting for Deep Metric Learning](https://arxiv.org/abs/1904.06627) (CVPR '19)\n- [Signal-to-Noise Ratio: A Robust Distance Metric for Deep Metric Learning](http://openaccess.thecvf.com/content_CVPR_2019/papers/Yuan_Signal-To-Noise_Ratio_A_Robust_Distance_Metric_for_Deep_Metric_Learning_CVPR_2019_paper.pdf) (CVPR '19)\n- [Divide and Conquer the Embedding Space for Metric Learning](http://openaccess.thecvf.com/content_CVPR_2019/papers/Sanakoyeu_Divide_and_Conquer_the_Embedding_Space_for_Metric_Learning_CVPR_2019_paper.pdf) (CVPR '19)\n- [Hardness-Aware Deep Metric Learning](http://openaccess.thecvf.com/content_CVPR_2019/papers/Zheng_Hardness-Aware_Deep_Metric_Learning_CVPR_2019_paper.pdf) (CVPR '19)\n- [Deep Metric Learning with Tuplet Margin Loss](http://openaccess.thecvf.com/content_ICCV_2019/papers/Yu_Deep_Metric_Learning_With_Tuplet_Margin_Loss_ICCV_2019_paper.pdf) (ICCV '19)\n- [SoftTriple Loss: Deep Metric Learning Without Triplet Sampling](http://openaccess.thecvf.com/content_ICCV_2019/papers/Qian_SoftTriple_Loss_Deep_Metric_Learning_Without_Triplet_Sampling_ICCV_2019_paper.pdf) (ICCV '19)\n- [Classification is a Strong Baseline for Deep Metric Learning](https://arxiv.org/abs/1811.12649) (BMVC '19)\n- [In Defense of the Classification Loss for Person Re-Identification](http://openaccess.thecvf.com/content_CVPRW_2019/papers/TRMTMCT/Zhai_In_Defense_of_the_Classification_Loss_for_Person_Re-Identification_CVPRW_2019_paper.pdf) (CVPRW '19)\n\n### 2020\n- [Circle Loss: A Unified Perspective of Pair Similarity Optimization](https://arxiv.org/abs/2002.10857) (CVPR '20)\n- [Proxy Anchor Loss for Deep Metric Learning](https://arxiv.org/abs/2003.13911) (CVPR '20)\n- [A Simple Framework for Contrastive Learning of Visual Representations](https://arxiv.org/abs/2002.05709)\n\n\n### Tools\n- https://github.com/KevinMusgrave/pytorch-metric-learning\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fadamdad%2Fawesome-metrics-learning","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fadamdad%2Fawesome-metrics-learning","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fadamdad%2Fawesome-metrics-learning/lists"}