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Source code of the paper: Spatio-Temporal Co-Attention Fusion Network for Video Splicing Localization, JEI 2024.

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Spatio-Temporal Co-Attention Fusion Network for Video Splicing Localization

An official implementation code for paper "Spatio-Temporal Co-Attention Fusion Network for Video Splicing Localization", JEI 2024. This repo will provide codes, trained weights, and our training datasets.

Network Architecture

architecture

Usage of SCFNet

  1. Configure the environment according to requirements.txt.
  2. Change the data path in train.py file.
  3. Run code for model training: python train.py

License

The code and dataset is released only for academic research. Commercial usage is strictly prohibited.

Citation

@article{Lin2024SCFNet,
author = {Man Lin and Gang Cao and Zijie Lou and Chi Zhang},
title = {{Spatio-temporal co-attention fusion network for video splicing localization}},
volume = {33},
journal = {Journal of Electronic Imaging},
number = {3},
publisher = {SPIE},
pages = {033027},
year = {2024},
doi = {10.1117/1.JEI.33.3.033027},
URL = {https://doi.org/10.1117/1.JEI.33.3.033027}
}

Contact

If you have any questions, please contact me(lyan924@cuc.edu.cn).

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Source code of the paper: Spatio-Temporal Co-Attention Fusion Network for Video Splicing Localization, JEI 2024.

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