deep-person-reid/docs/AWESOME_REID.md

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# Awesome-ReID
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Here is a collection of ReID-related research with links to papers and code. You are welcome to submit [PR](https://help.github.com/articles/creating-a-pull-request/)s if you find something missing.
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## Conferences
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- **[ICCV 2019](#iccv-2019)**
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- **[CVPR 2019](#cvpr-2019)**
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- **[AAAI 2019](#aaai-2019)**
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- **[NeurIPS 2018](#neurips-2018)**
- **[ECCV 2018](#eccv-2018)**
- **[CVPR 2018](#cvpr-2018)**
- **[ArXiv](#arxiv)**
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### ICCV 2019
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- 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)] [[code](https://github.com/wangguanan/AlignGAN)]
- Unsupervised Graph Association for Person Re-identification. [[paper](https://github.com/yichuan9527/Unsupervised-Graph-Association-for-Person-Re-identification)] [[code](https://github.com/yichuan9527/Unsupervised-Graph-Association-for-Person-Re-identification)]
- 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)] [[code](https://github.com/OasisYang/SSG)]
- 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)] [[code](https://github.com/LuckyDC/SFT_REID)]
- 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)] [[code](https://github.com/ggjy/P2Net.pytorch)]
- 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)][[code](https://github.com/InnovArul/vidreid_cosegmentation)]
- Mixed High-Order Attention Network for Person Re-Identification. [[paper](https://arxiv.org/abs/1908.05819)][[code](https://github.com/chenbinghui1/MHN)]
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- ABD-Net: Attentive but Diverse Person Re-Identification. [[paper](https://arxiv.org/abs/1908.01114)] [[code](https://github.com/TAMU-VITA/ABD-Net)]
- Omni-Scale Feature Learning for Person Re-Identification. [[paper](https://arxiv.org/abs/1905.00953)] [[code](https://github.com/KaiyangZhou/deep-person-reid)]
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### CVPR 2019
- Joint Discriminative and Generative Learning for Person Re-identification. [[paper](https://arxiv.org/abs/1904.07223)][[code](https://github.com/NVlabs/DG-Net)]
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- Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification. [[paper](https://arxiv.org/abs/1904.01990)][[code](https://github.com/zhunzhong07/ECN)]
- Dissecting Person Re-identification from the Viewpoint of Viewpoint. [[paper](https://arxiv.org/abs/1812.02162)][[code](https://github.com/sxzrt/Dissecting-Person-Re-ID-from-the-Viewpoint-of-Viewpoint)]
- Unsupervised Person Re-identification by Soft Multilabel Learning. [[paper](https://arxiv.org/abs/1903.06325)][[code](https://github.com/KovenYu/MAR)]
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- Patch-based Discriminative Feature Learning for Unsupervised Person Re-identification. [[paper](https://kovenyu.com/publication/2019-cvpr-pedal/)][[code](https://github.com/QizeYang/PAUL)]
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### AAAI 2019
- Spatial and Temporal Mutual Promotion for Video-based Person Re-identification. [[paper](https://arxiv.org/abs/1812.10305)][[code](https://github.com/yolomax/person-reid-lib)]
- Spatial-Temporal Person Re-identification. [[paper](https://arxiv.org/abs/1812.03282)][[code](https://github.com/Wanggcong/Spatial-Temporal-Re-identification)]
- Horizontal Pyramid Matching for Person Re-identification. [[paper](https://arxiv.org/abs/1804.05275)][[code](https://github.com/OasisYang/HPM)]
- Backbone Can Not be Trained at Once: Rolling Back to Pre-trained Network for Person Re-identification. [[paper](https://arxiv.org/abs/1901.06140)][[code](https://github.com/youngminPIL/rollback)]
- A Bottom-Up Clustering Approach to Unsupervised Person Re-identification. [[paper](https://vana77.github.io/vana77.github.io/images/AAAI19.pdf)][[code](https://github.com/vana77/Bottom-up-Clustering-Person-Re-identification)]
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### NeurIPS 2018
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- FD-GAN: Pose-guided Feature Distilling GAN for Robust Person Re-identification. [[paper](https://arxiv.org/abs/1810.02936)][[code](https://github.com/yxgeee/FD-GAN)]
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### ECCV 2018
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- 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)][[code](https://github.com/zhunzhong07/HHL)]
- Pose-Normalized Image Generation for Person Re-identification. [[paper](https://arxiv.org/abs/1712.02225)][[code](https://github.com/naiq/PN_GAN)]
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### CVPR 2018
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- Camera Style Adaptation for Person Re-Identification. [[paper](https://arxiv.org/abs/1711.10295)][[code](https://github.com/zhunzhong07/CamStyle)]
- Deep Group-Shuffling Random Walk for Person Re-Identification. [[paper](https://arxiv.org/abs/1807.11178)][[code](https://github.com/YantaoShen/kpm_rw_person_reid)]
- End-to-End Deep Kronecker-Product Matching for Person Re-identification. [[paper](https://arxiv.org/abs/1807.11182)][[code](https://github.com/YantaoShen/kpm_rw_person_reid)]
- Features for Multi-Target Multi-Camera Tracking and Re-Identification. [[paper](https://arxiv.org/abs/1803.10859)][[code](https://github.com/ergysr/DeepCC)]
- Group Consistent Similarity Learning via Deep CRF for Person Re-Identification. [[paper](http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Group_Consistent_Similarity_CVPR_2018_paper.pdf)][[code](https://github.com/dapengchen123/crf_affinity)]
- Harmonious Attention Network for Person Re-Identification. [[paper](https://arxiv.org/abs/1802.08122)][[code](https://github.com/KaiyangZhou/deep-person-reid)]
- Human Semantic Parsing for Person Re-Identification. [[paper](https://arxiv.org/abs/1804.00216)][[code](https://github.com/emrahbasaran/SPReID)]
- Multi-Level Factorisation Net for Person Re-Identification. [[paper](https://arxiv.org/abs/1803.09132)][[code](https://github.com/KaiyangZhou/deep-person-reid)]
- Resource Aware Person Re-identification across Multiple Resolutions. [[paper](https://arxiv.org/abs/1805.08805)][[code](https://github.com/mileyan/DARENet)]
- Exploit the Unknown Gradually: One-Shot Video-Based Person Re-Identification by Stepwise Learning. [[paper](https://yu-wu.net/pdf/CVPR2018_Exploit-Unknown-Gradually.pdf)][[code](https://github.com/Yu-Wu/Exploit-Unknown-Gradually)]
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### ArXiv
- Revisiting Temporal Modeling for Video-based Person ReID. [[paper](https://arxiv.org/abs/1805.02104)][[code](https://github.com/jiyanggao/Video-Person-ReID)]
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- Learning Generalisable Omni-Scale Representations for Person Re-Identification [[paper](https://arxiv.org/abs/1910.06827)][[code](https://github.com/KaiyangZhou/deep-person-reid)]