---
task_categories:
- text-to-video
---

# RefVIE-Bench

[**Project Page**](https://showlab.github.io/Kiwi-Edit/) | [**Paper**](https://arxiv.org/abs/2603.02175) | [**GitHub**](https://github.com/showlab/Kiwi-Edit)

RefVIE-Bench is a comprehensive evaluation benchmark introduced in the paper [Kiwi-Edit: Versatile Video Editing via Instruction and Reference Guidance](https://arxiv.org/abs/2603.02175). It is specifically designed to assess instruction-reference-following capabilities in video editing models, featuring source videos, reference images (for both subjects and backgrounds), and natural language instructions.

## Sample Usage

To run inference on this benchmark using the official Kiwi-Edit framework, you can use the following command:

```bash
python infer.py \
  --ckpt_path path_to_ckpt \
  --bench refvie \
  --max_frame 81 \
  --max_pixels 921600 \
  --save_dir ./infer_results/exp_name/
```

## Directory layout

- `refvie_bench.yaml`: Configuration file containing mapping for instructions, reference images, and source videos.
- `ref_images/background/`: Reference images used for background-guided editing.
- `ref_images/subjects/`: Reference images used for subject-guided editing.
- `source_videos/`: The original video sequences.

## Included media

- Total referenced media files: 86
- Reference images: 54
  - Background images: 8
  - Subject images: 46
- Source videos: 32

## Notes

- File paths in `refvie_bench.yaml` are preserved relative to this release directory.

## Citation

If you use our code in your work, please cite [our paper](https://arxiv.org/abs/2603.02175):

```bibtex
@misc{kiwiedit,
      title={Kiwi-Edit: Versatile Video Editing via Instruction and Reference Guidance}, 
      author={Yiqi Lin and Guoqiang Liang and Ziyun Zeng and Zechen Bai and Yanzhe Chen and Mike Zheng Shou},
      year={2026},
      eprint={2603.02175},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2603.02175}, 
}
```