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[CVPR 2022 Oral] Detecting Deepfakes with Self-Blended Images https://arxiv.org/abs/2204.08376

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I follow the settings in 4.1. Implementation Details and try to train a detector on FF+ raw with only real faces and self-blend fake faces. However when testing on FF+...

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...

Hi, I ran the code in (build.sh) by cmd then executor failed running and created a container by code in (exec.sh) i don't know it's function, was there any wrong...

As specified in the commits the relevant changes are: - **src/inference/inference_image.py** - Remove the double _**os**_ library import, add the _**cv2**_ library that is missing - **dockerfiles/Dockerfile** - Modify image...

Thanks for the great work, I have some questions about "exist_bi", the AUC on CDF before using the landmark augmentation code was 82%, but after using the landmark augmentation code...

can you release training code of CDF?

In paper 4.4. Cross-Manipulation Evaluation,“We use the raw version for evaluation as well as the competitors.” but the most of the CVPR2021 and ICCV21 papers all use the c23 as...

Could you please share the code for visual detection of pictures with GradCma++?

You shared in your paper that you implemented your algorithm together with GradCam++, could you share this code as well please?

Hi, I have my face dataset ready and wish not to perform duplicate face detection during inference as it brings huge time cost. However, when I commented out the face...