MGH.pytorch

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[ACM MM2021] MGH: Metadata Guided Hypergraph Modeling for Unsupervised Person Re-identification

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// repository documentation

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### Introduction

This project is developed based on [FastReID](https://github.com/JDAI-CV/fast-reid), which is an ongoing ReID project.

### Projects

#### BUC
In projects/BUC, we implement AAAI 2019 paper **A Bottom-Up Clustering Approach to Unsupervised Person Re-Identification**. The original implementation is in [BUC](https://github.com/vana77/Bottom-up-Clustering-Person-Re-identification).

#### SpCL
In projects/SpCL, we implement NeurIPS 2020 paper **Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID**. The original implementation is in [SpCL](https://github.com/yxgeee/SpCL/).

#### HCT
In projects/HCT, we implement CVPR 2020 paper **Hierarchical Clustering with Hard-batch Triplet Loss for Person Re-identification**. The original implementation is in [HCT](https://github.com/zengkaiwei/HCT)

#### MGH
In projects/MGH, we implement ACM MM 2021 paper **MGH: Metadata Guided Hypergraph Modeling for Unsupervised Person Re-identification**. Please refer [it's README](https://github.com/weleen/MGH.pytorch/blob/code/projects/MGH/README.md) for more details. [Paper](https://arxiv.org/abs/2110.05886)

### Citation

Please cite our work:

```latex
@inproceedings{wu2021mgh,
  author    = {Yiming Wu and
               Xintian Wu and 
               Jian Tian and 
               Xi Li},
  title     = {MGH: Metadata Guided Hypergraph Modeling for Unsupervised Person Re-identification},
  booktitle = ACMMM,
  year      = 2021,
  publisher = {{ACM}}}
```

MGH.pytorch

MGH.pytorch 최신버젼 다운로드

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