1. Setup repository and environment

   git clone git@github.com:FudanCVL/EffectErase.git
   cd EffectErase
   pip install -e .

2. Download weights

   hf download alibaba-pai/Wan2.1-Fun-1.3B-InP --local-dir Wan-AI/Wan2.1-Fun-1.3B-InP
   hf download FudanCVL/EffectErase EffectErase.ckpt --local-dir ./

3. Run the script

   bash script/test_remove.sh

   You can edit script/test_remove.sh and change these three paths to use your own data:

   • --fg_bg_path
   • --mask_path
   • --output_path

   --mask_path is a mask video generated by SAM2.1 (sam2.1_hiera_b+), aligned with --fg_bg_path.

Please consider to cite:

@inproceedings{fu2026EffectErase,
  title={{EffectErase}: Joint Video Object Removal and Insertion for High-Quality Effect Erasing},
  author={Fu, Yang and Zheng, Yike and Dai, Ziyun and Ding, Henghui},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2026}
}

If you have any questions, please feel free to reach me out at aleeyanger@gmail.com.

This code is based on DiffSynth-Studio. Thanks for their awesome works！

This project is licensed under CC BY-NC 4.0.

For research purposes only. Commercial use is strictly prohibited.