# SINet

**Repository Path**: teslatasy/SINet

## Basic Information

- **Project Name**: SINet
- **Description**: github上的，国内网络问题
原始网址：https://github.com/baist/SINet
侵删。
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2023-01-23
- **Last Updated**: 2023-01-23

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

### A codebase for video-based person re-identification

Salient-to-Broad Transition for Video Person Re-identification (CVPR 2022)

SANet: Statistic Attention Network for Video-Based Person Re-Identification (TCSVT 2021)

### Get started

```Shell
  # Train
  python main.py \
   --arch ${sinet, sbnet, idnet, sanet} \
   --dataset ${mars, lsvid, ...} \
   --root ${path of dataset} \
   --gpu_devices 0,1 \
   --save_dir ${path for saving modles and logs} \
  
  # Test with all frames
  python main.py \
   --arch ${sinet, sbnet, idnet, sanet} \
   --dataset mars \
   --root ${path of dataset} \
   --gpu_devices 0,1 \
   --save_dir ${path for saving logs} \
   --evaluate --all_frames --resume ${path of pretrained model}
  ```
  

### Pretrained models

#### MARS
|     Methods                   | Paper | Reproduce | Download |
|----- | -----| ----- | -----| 
| SBNet (ResNet50 + SBM)        | 85.7/90.2 | 85.6/90.7 | [model](https://drive.google.com/file/d/1l0VeAzZ1-Z7Gbrp6jLuF_C6MIAiamrpQ/view?usp=sharing) | 
| IDNet (Resnet50 + IDM)        | 85.9/90.5 | 85.9/90.4 | [model](https://drive.google.com/file/d/1XxJUxaUXDDB1cq6d6W5aGfwj54OvqW5N/view?usp=sharing) |
| **SINet** (ResNet50 + SBM + IDM)  | 86.2/91.0 | 86.3/90.9 | [model](https://drive.google.com/file/d/18YKaBdexzc49A-zhmT8vJY_xug_eLiYF/view?usp=sharing) | 
| **SANet** (ResNet50 + SA Block) | 86.0/91.2 | 86.7/91.2 | [model](https://drive.google.com/file/d/1yhX4trD02-ryJ7jRObstmHk9IZb9Smc3/view?usp=sharing) | 


#### LS-VID

|     Methods                   | Paper | Reproduce | Download |
|----- | -----| ----- | -----| 
| SBNet (ResNet50 + SBM)        | 77.1/85.1 | 77.2/85.3 | [model](https://drive.google.com/file/d/1bAxPRKoFoLluP3dVpzpsEJCY_kJhaL2v/view?usp=sharing) | 
| IDNet (Resnet50 + IDM)        | 78.0/86.2 | 78.2/86.0 | [model](https://drive.google.com/file/d/1l-vH5huoodRjiNBbfWAZIjLdXekAi70X/view?usp=sharing) |
| **SINet** (ResNet50 + SBM + IDM)  | 79.6/87.4 | 79.9/87.2 | [model](https://drive.google.com/file/d/1Xdd_XUPyhbrrB06wDq_qUdUzMKdjD9FK/view?usp=sharing) | 

### Citation

If you use our code in your research or wish to refer to the baseline results, please use the following BibTeX entry.

    @inproceedings{bai2022SINet,
        title={Salient-to-Broad Transition for Video Person Re-identification},
        author={Bai, Shutao and Ma, Bingpeng and Chang, Hong and Huang, Rui and Chen, Xilin},
        booktitle={CVPR},
        year={2022},
    }

    @ARTICLE{9570321,
      author={Bai, Shutao and Ma, Bingpeng and Chang, Hong and Huang, Rui and Shan, Shiguang and Chen, Xilin},
      journal={IEEE Transactions on Circuits and Systems for Video Technology}, 
      title={SANet: Statistic Attention Network for Video-Based Person Re-Identification}, 
      year={2021},
      volume={},
      number={},
      pages={1-1},
      doi={10.1109/TCSVT.2021.3119983}
    }

### Acknowledgments

This code is based on the implementations of [**AP3D**](https://github.com/guxinqian/AP3D).