Forgery
收藏魔搭社区2025-10-22 更新2025-07-26 收录
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https://modelscope.cn/datasets/duoquduoqu/Forgery
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# Selective Domain-Invariant Feature for Generalizable Deepfake Detection
Pytorch implementation of "Selective Domain-Invariant Feature for Generalizable Deepfake Detection"
## Prerequisites:
torch: 1.5.1
numpy: 1.19.0
scikit-image: 0.17.2
scikit-learn: 0.23.1
scipy: 1.5.1
# Citation
```
@inproceedings{lai2024selective,
title={Selective domain-invariant feature for generalizable deepfake detection},
author={Lai, Yingxin and Yang, Guoqing and He, Yifan and Luo, Zhiming and Li, Shaozi},
booktitle={ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
pages={2335--2339},
year={2024},
organization={IEEE}
}
```
# 面向可泛化深度伪造检测的选择性域不变特征
本文《面向可泛化深度伪造检测的选择性域不变特征》的PyTorch实现
## 前置依赖:
torch 1.5.1
numpy 1.19.0
scikit-image 0.17.2
scikit-learn 0.23.1
scipy 1.5.1
# 引用格式
@inproceedings{lai2024selective,
title={选择性域不变特征用于可泛化深度伪造检测},
author={赖颖昕、杨国庆、贺一凡、罗智明、李少孜},
booktitle={ICASSP 2024——2024年IEEE国际声学、语音与信号处理会议(ICASSP 2024)},
pages={2335–2339},
year={2024},
organization={IEEE}
}
提供机构:
maas
创建时间:
2025-07-25



