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<li class="toctree-l3"><a class="reference internal" href="#iccv-2019">ICCV 2019</a></li>
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<li class="toctree-l3"><a class="reference internal" href="#cvpr-2019">CVPR 2019</a></li>
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<li class="toctree-l3"><a class="reference internal" href="#aaai-2019">AAAI 2019</a></li>
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<li class="toctree-l3"><a class="reference internal" href="#eccv-2018">ECCV 2018</a></li>
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<div class="section" id="awesome-reid">
<h1>Awesome-ReID<a class="headerlink" href="#awesome-reid" title="Permalink to this headline"></a></h1>
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<p>Here is a collection of ReID-related research with links to papers and code. You are welcome to submit <a class="reference external" href="https://help.github.com/articles/creating-a-pull-request/">PR</a>s if you find something missing.</p>
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<div class="section" id="conferences">
<h2>Conferences<a class="headerlink" href="#conferences" title="Permalink to this headline"></a></h2>
<ul class="simple">
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<li><strong><a class="reference external" href="#iccv-2019">ICCV 2019</a></strong></li>
<li><strong><a class="reference external" href="#cvpr-2019">CVPR 2019</a></strong></li>
<li><strong><a class="reference external" href="#aaai-2019">AAAI 2019</a></strong></li>
<li><strong><a class="reference external" href="#neurips-2018">NeurIPS 2018</a></strong></li>
<li><strong><a class="reference external" href="#eccv-2018">ECCV 2018</a></strong></li>
<li><strong><a class="reference external" href="#cvpr-2018">CVPR 2018</a></strong></li>
<li><strong><a class="reference external" href="#arxiv">ArXiv</a></strong></li>
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</ul>
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<div class="section" id="iccv-2019">
<h3>ICCV 2019<a class="headerlink" href="#iccv-2019" title="Permalink to this headline"></a></h3>
<ul class="simple">
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<li>RGB-Infrared Cross-Modality Person Re-Identification via Joint Pixel and Feature Alignment. [<a class="reference external" href="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">paper</a>] [<a class="reference external" href="https://github.com/wangguanan/AlignGAN">code</a>]</li>
<li>Unsupervised Graph Association for Person Re-identification. [<a class="reference external" href="https://github.com/yichuan9527/Unsupervised-Graph-Association-for-Person-Re-identification">paper</a>] [<a class="reference external" href="https://github.com/yichuan9527/Unsupervised-Graph-Association-for-Person-Re-identification">code</a>]</li>
<li>Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-identification. [<a class="reference external" href="http://openaccess.thecvf.com/content_ICCV_2019/papers/Fu_Self-Similarity_Grouping_A_Simple_Unsupervised_Cross_Domain_Adaptation_Approach_for_ICCV_2019_paper.pdf">paper</a>] [<a class="reference external" href="https://github.com/OasisYang/SSG">code</a>]</li>
<li>Spectral Feature Transformation for Person Re-Identification. [<a class="reference external" href="http://openaccess.thecvf.com/content_ICCV_2019/papers/Luo_Spectral_Feature_Transformation_for_Person_Re-Identification_ICCV_2019_paper.pdf">paper</a>] [<a class="reference external" href="https://github.com/LuckyDC/SFT_REID">code</a>]</li>
<li>Beyond Human Parts: Dual Part-Aligned Representations for Person Re-Identification. [<a class="reference external" href="http://openaccess.thecvf.com/content_ICCV_2019/papers/Guo_Beyond_Human_Parts_Dual_Part-Aligned_Representations_for_Person_Re-Identification_ICCV_2019_paper.pdf">paper</a>] [<a class="reference external" href="https://github.com/ggjy/P2Net.pytorch">code</a>]</li>
<li>Co-segmentation Inspired Attention Networks for Video-based Person Re-identification. [<a class="reference external" href="http://openaccess.thecvf.com/content_ICCV_2019/papers/Subramaniam_Co-Segmentation_Inspired_Attention_Networks_for_Video-Based_Person_Re-Identification_ICCV_2019_paper.pdf">paper</a>][<a class="reference external" href="https://github.com/InnovArul/vidreid_cosegmentation">code</a>]</li>
<li>Mixed High-Order Attention Network for Person Re-Identification. [<a class="reference external" href="https://arxiv.org/abs/1908.05819">paper</a>][<a class="reference external" href="https://github.com/chenbinghui1/MHN">code</a>]</li>
<li>ABD-Net: Attentive but Diverse Person Re-Identification. [<a class="reference external" href="https://arxiv.org/abs/1908.01114">paper</a>] [<a class="reference external" href="https://github.com/TAMU-VITA/ABD-Net">code</a>]</li>
<li>Omni-Scale Feature Learning for Person Re-Identification. [<a class="reference external" href="https://arxiv.org/abs/1905.00953">paper</a>] [<a class="reference external" href="https://github.com/KaiyangZhou/deep-person-reid">code</a>]</li>
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</ul>
</div>
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<div class="section" id="cvpr-2019">
<h3>CVPR 2019<a class="headerlink" href="#cvpr-2019" title="Permalink to this headline"></a></h3>
<ul class="simple">
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<li>Joint Discriminative and Generative Learning for Person Re-identification. [<a class="reference external" href="https://arxiv.org/abs/1904.07223">paper</a>][<a class="reference external" href="https://github.com/NVlabs/DG-Net">code</a>]</li>
<li>Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification. [<a class="reference external" href="https://arxiv.org/abs/1904.01990">paper</a>][<a class="reference external" href="https://github.com/zhunzhong07/ECN">code</a>]</li>
<li>Dissecting Person Re-identification from the Viewpoint of Viewpoint. [<a class="reference external" href="https://arxiv.org/abs/1812.02162">paper</a>][<a class="reference external" href="https://github.com/sxzrt/Dissecting-Person-Re-ID-from-the-Viewpoint-of-Viewpoint">code</a>]</li>
<li>Unsupervised Person Re-identification by Soft Multilabel Learning. [<a class="reference external" href="https://arxiv.org/abs/1903.06325">paper</a>][<a class="reference external" href="https://github.com/KovenYu/MAR">code</a>]</li>
<li>Patch-based Discriminative Feature Learning for Unsupervised Person Re-identification. [<a class="reference external" href="https://kovenyu.com/publication/2019-cvpr-pedal/">paper</a>][<a class="reference external" href="https://github.com/QizeYang/PAUL">code</a>]</li>
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</ul>
</div>
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<div class="section" id="aaai-2019">
<h3>AAAI 2019<a class="headerlink" href="#aaai-2019" title="Permalink to this headline"></a></h3>
<ul class="simple">
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<li>Spatial and Temporal Mutual Promotion for Video-based Person Re-identification. [<a class="reference external" href="https://arxiv.org/abs/1812.10305">paper</a>][<a class="reference external" href="https://github.com/yolomax/person-reid-lib">code</a>]</li>
<li>Spatial-Temporal Person Re-identification. [<a class="reference external" href="https://arxiv.org/abs/1812.03282">paper</a>][<a class="reference external" href="https://github.com/Wanggcong/Spatial-Temporal-Re-identification">code</a>]</li>
<li>Horizontal Pyramid Matching for Person Re-identification. [<a class="reference external" href="https://arxiv.org/abs/1804.05275">paper</a>][<a class="reference external" href="https://github.com/OasisYang/HPM">code</a>]</li>
<li>Backbone Can Not be Trained at Once: Rolling Back to Pre-trained Network for Person Re-identification. [<a class="reference external" href="https://arxiv.org/abs/1901.06140">paper</a>][<a class="reference external" href="https://github.com/youngminPIL/rollback">code</a>]</li>
<li>A Bottom-Up Clustering Approach to Unsupervised Person Re-identification. [<a class="reference external" href="https://vana77.github.io/vana77.github.io/images/AAAI19.pdf">paper</a>][<a class="reference external" href="https://github.com/vana77/Bottom-up-Clustering-Person-Re-identification">code</a>]</li>
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</ul>
</div>
<div class="section" id="neurips-2018">
<h3>NeurIPS 2018<a class="headerlink" href="#neurips-2018" title="Permalink to this headline"></a></h3>
<ul class="simple">
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<li>FD-GAN: Pose-guided Feature Distilling GAN for Robust Person Re-identification. [<a class="reference external" href="https://arxiv.org/abs/1810.02936">paper</a>][<a class="reference external" href="https://github.com/yxgeee/FD-GAN">code</a>]</li>
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</ul>
</div>
<div class="section" id="eccv-2018">
<h3>ECCV 2018<a class="headerlink" href="#eccv-2018" title="Permalink to this headline"></a></h3>
<ul class="simple">
update readme
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<li>Generalizing A Person Retrieval Model Hetero- and Homogeneously. [<a class="reference external" href="http://openaccess.thecvf.com/content_ECCV_2018/papers/Zhun_Zhong_Generalizing_A_Person_ECCV_2018_paper.pdf">paper</a>][<a class="reference external" href="https://github.com/zhunzhong07/HHL">code</a>]</li>
<li>Pose-Normalized Image Generation for Person Re-identification. [<a class="reference external" href="https://arxiv.org/abs/1712.02225">paper</a>][<a class="reference external" href="https://github.com/naiq/PN_GAN">code</a>]</li>
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</ul>
</div>
<div class="section" id="cvpr-2018">
<h3>CVPR 2018<a class="headerlink" href="#cvpr-2018" title="Permalink to this headline"></a></h3>
<ul class="simple">
update readme
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<li>Camera Style Adaptation for Person Re-Identification. [<a class="reference external" href="https://arxiv.org/abs/1711.10295">paper</a>][<a class="reference external" href="https://github.com/zhunzhong07/CamStyle">code</a>]</li>
<li>Deep Group-Shuffling Random Walk for Person Re-Identification. [<a class="reference external" href="https://arxiv.org/abs/1807.11178">paper</a>][<a class="reference external" href="https://github.com/YantaoShen/kpm_rw_person_reid">code</a>]</li>
<li>End-to-End Deep Kronecker-Product Matching for Person Re-identification. [<a class="reference external" href="https://arxiv.org/abs/1807.11182">paper</a>][<a class="reference external" href="https://github.com/YantaoShen/kpm_rw_person_reid">code</a>]</li>
<li>Features for Multi-Target Multi-Camera Tracking and Re-Identification. [<a class="reference external" href="https://arxiv.org/abs/1803.10859">paper</a>][<a class="reference external" href="https://github.com/ergysr/DeepCC">code</a>]</li>
<li>Group Consistent Similarity Learning via Deep CRF for Person Re-Identification. [<a class="reference external" href="http://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_Group_Consistent_Similarity_CVPR_2018_paper.pdf">paper</a>][<a class="reference external" href="https://github.com/dapengchen123/crf_affinity">code</a>]</li>
<li>Harmonious Attention Network for Person Re-Identification. [<a class="reference external" href="https://arxiv.org/abs/1802.08122">paper</a>][<a class="reference external" href="https://github.com/KaiyangZhou/deep-person-reid">code</a>]</li>
<li>Human Semantic Parsing for Person Re-Identification. [<a class="reference external" href="https://arxiv.org/abs/1804.00216">paper</a>][<a class="reference external" href="https://github.com/emrahbasaran/SPReID">code</a>]</li>
<li>Multi-Level Factorisation Net for Person Re-Identification. [<a class="reference external" href="https://arxiv.org/abs/1803.09132">paper</a>][<a class="reference external" href="https://github.com/KaiyangZhou/deep-person-reid">code</a>]</li>
<li>Resource Aware Person Re-identification across Multiple Resolutions. [<a class="reference external" href="https://arxiv.org/abs/1805.08805">paper</a>][<a class="reference external" href="https://github.com/mileyan/DARENet">code</a>]</li>
<li>Exploit the Unknown Gradually: One-Shot Video-Based Person Re-Identification by Stepwise Learning. [<a class="reference external" href="https://yu-wu.net/pdf/CVPR2018_Exploit-Unknown-Gradually.pdf">paper</a>][<a class="reference external" href="https://github.com/Yu-Wu/Exploit-Unknown-Gradually">code</a>]</li>
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</ul>
</div>
<div class="section" id="arxiv">
<h3>ArXiv<a class="headerlink" href="#arxiv" title="Permalink to this headline"></a></h3>
<ul class="simple">
update readme
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<li>Revisiting Temporal Modeling for Video-based Person ReID. [<a class="reference external" href="https://arxiv.org/abs/1805.02104">paper</a>][<a class="reference external" href="https://github.com/jiyanggao/Video-Person-ReID">code</a>]</li>
<li>Learning Generalisable Omni-Scale Representations for Person Re-Identification [<a class="reference external" href="https://arxiv.org/abs/1910.06827">paper</a>][<a class="reference external" href="https://github.com/KaiyangZhou/deep-person-reid">code</a>]</li>
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