3 accepted papers
The rapid advancement of diffusion models has significantly improved high-quality image generation, making generated content increasingly challenging to distinguish from real images and raising concerns about potential misuse. In this paper, we observe that diffusion models struggle to accurately re…
The rapid development of deepfake technology poses a formidable challenge to personal privacy and security, underscoring the urgent need for deepfake detection. Recently, the methods based on the reconstruction error, such as DIRE and RECCE, achieve impressive performance in forgery detection. Howev…
As one of the prominent AI-generated content, Deepfake has raised significant safety concerns. Although it has been demonstrated that temporal consistency cues offer better generalization capability, existing methods based on CNNs inevitably introduce spatial bias, which hinders the extraction of in…