Datasets:
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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},
}
``` |