This is our new work about Face Forgery Detection, which has been accepted by ECCV 2022 (oral).
UIA-ViT: Unsupervised Inconsistency-Aware Method based on Vision Transformer for Face Forgery Detection
paper link: https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136650384.pdf
https://arxiv.org/abs/2210.12752
pytorch==1.6.0 torchvision==0.5.0 cudatoolkit==10.1 timm==0.4.12
Test code: test.py
Train code: train.py
Our trained model has been released: https://drive.google.com/drive/folders/1zPx4TLEfLnJDZYpSV0LhFvrMEEDzroB0?usp=sharing
Some main code about our proposed UPCL is in utils/utils.py.
Please cite the following paper in your publications if you use the python implementations:
@inproceedings{zhuang2020UIA,
title={UIA-ViT: Unsupervised Inconsistency-Aware Method based on Vision Transformer for Face Forgery Detection},
author={Zhuang, Wanyi and Chu, Qi and Tan, Zhentao and Liu, Qiankun and Yuan, Haojie and Miao, Changtao and Luo, Zixiang and Yu, Nenghai},
booktitle={European Conference on Computer Vision (ECCV)},
year={2022},
}