Kiwi-Edit
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Kiwi-Edit is a versatile video editing framework built on an MLLM encoder and a video Diffusion Transformer (DiT). It supports:
The model synergizes learnable queries and latent visual features for reference semantic guidance, achieving significant gains in instruction following and reference fidelity.
To use Kiwi-Edit for inference, follow the installation instructions in the official repository. You can run a quick test on a demo video using the following command:
python diffusers_demo.py \
--video_path ./demo_data/video/source/0005e4ad9f49814db1d3f2296b911abf.mp4 \
--prompt "Remove the monkey." \
--save_path output.mp4 --model_path linyq/kiwi-edit-5b-instruct-only-diffusers
If you use Kiwi-Edit in your research, please cite the following work:
@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},
}