The AUC of FF++(c23)

[WeinanGuan]

I run the inference on Celeb-DF-v2, and FF++ (c23) with your pre-trained model. I get the similar results on the former (AUC:0.9381, AP:0.9669). However, the video-level AUC on the latter is only 0.9051, and AP is 0.9797. I also separately test the performance on Deepfakes, FaceSwap, Face2Face, NeuralTextures and FaceShifter. The results are as follows: DF-AUC:0.9856/AP:0.9900; FS-AUC:0.9698/AP:0.9747; F2F-AUC:0.9094/AP:0.9192; NT-AUC:0.8254/AP:0.8427; FSh-AUC:0.8351/AP:0.8427. Except for Deepfakes, other performance has some difference with that your reported in the supplementary. Do you run the inference on FF++ c23 dataset? I do not think the c23 videos can result the significant performance drop. Would you like to provide some suggestions to solve this problem?