# CiSIN

**Repository Path**: anruoran/CiSIN

## Basic Information

- **Project Name**: CiSIN
- **Description**: 将ReID技术用于视频人物关联与角色理解
Character Grounding and Re-Identification in Story of Videos and Text Descriptions
作者 | Youngjae Yu, Jongseok Kim, Heeseung Yun, Jiwan Chung, Gunhee Kim
单位 | 首尔大学；Ripple AI
论文 | https://www.ecva.net/papers/eccv_2020/
papers_ECCV/papers/123500528.pdf
代码 | https://github.com/yj-yu/CiSIN
备注 | ECCV 2020 Spotlight
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-10-02
- **Last Updated**: 2024-06-04

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Character in Story Identification Network (CiSIN)

This project hosts the code for our paper.

- [Youngjae Yu](https://yj-yu.github.io/home), Jongseok Kim, Heeseung Yun, Jiwan Chung and [Gunhee Kim](http://vision.snu.ac.kr/~gunhee/).
Character Grounding and Re-Identification inStory of Videos and Text Descriptions. In *ECCV* (spotlight), 2020.

This project is an Winning Solution in LSMDC 19 ["Fill-in the Characters"](https://sites.google.com/site/describingmovies/lsmdc-2019/challenge-details?authuser=0) task.
For more information about the LSMDC visit the [Large Scale Movie Description Challenge (LSMDC) 2019](https://sites.google.com/site/describingmovies/lsmdc-2019)

## Reference

If you use this code as part of any published research, please refer following paper,

```bibtex
@inproceedings{yu:2020:ECCV,
    title="{Character Grounding and Re-Identification inStory of Videos and Text Descriptions}",
    author={Yu, Youngjae and Kim, Jongseok and Yun, Heeseung and Chung Jiwan and Kim, Gunhee},
    booktitle={ECCV},
    year=2020
}
```

## System Requirements

The following dependencies should be installed:

- Python 3.6
- Pytorch 1.4.0
- torchvision 0.5.0
- CUDA 10.0 supported GPU with at least 12GB memory
- see [requirements.txt](requirements.txt) for more details

## Data Setup

Coming soon,

## Running Experiments

### Feature Extraction

Coming soon,


### CiSIN

To train our model,
```bash
python train.py
```

Coming soon,


## Acknowledgement

We thank SNUVL lab members for helpful comments.
This research was supported by Seoul National University, Brain Research Program by National Research Foundation of Korea (NRF) (2017M3C7A1047860), and AIR Lab (AI Research Lab) in Hyundai Motor Company through HMC-SNU AI Consortium Fund.


## License

[LICENSE.md](LICENSE.md).