6 citations · 7 across the 5 of their papers we have counts for
5 papers
Delocate: Detection and Localization for Deepfake Videos with Randomly-Located Tampered Traces
Juan Hu, Xin Liao, Difei Gao +4
Deepfake videos are becoming increasingly realistic, showing few tampering traces on facial areasthat vary between frames. Consequently, existing Deepfake detection methods struggl…
Recap: Detecting Deepfake Video with Unpredictable Tampered Traces via Recovering Faces and Mapping Recovered Faces
Juan Hu, Xin Liao, Difei Gao +4
The exploitation of Deepfake techniques for malicious intentions has driven significant research interest in Deepfake detection. Deepfake manipulations frequently introduce random…
Mover: Mask and Recovery based Facial Part Consistency Aware Method for Deepfake Video Detection
Juan Hu, Xin Liao, Difei Gao +4
Deepfake techniques have been widely used for malicious purposes, prompting extensive research interest in developing Deepfake detection methods. Deepfake manipulations typically i…
Mover: Mask and Recovery based Facial Part Consistency Aware Method for Deepfake Video Detection
Juan Hu, Xin Liao, Difei Gao +4
Deepfake techniques have been widely used for malicious purposes, prompting extensive research interest in developing Deepfake detection methods. Deepfake manipulations typically i…
Unsupervised Voice-Face Representation Learning by Cross-Modal Prototype Contrast
Boqing Zhu, Kele Xu, Changjian Wang +4
We present an approach to learn voice-face representations from the talking face videos, without any identity labels. Previous works employ cross-modal instance discrimination task…