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Self-Supervised Video Forensics by Audio-Visual Anomaly Detection Chao Feng, Ziyang Chen, Andrew Owens University of Michigan, Ann Arbor
Beijing Jiaotong University, YanShan University, A*Star
The code of multi-attention deepfake detection pretrained models and preprocessing method can be access here https://drive.google.com/file/d/1lYyUe99Goh1YCilt1IOiD9oMO6ig8j1o/view?usp=sharing
The main features of yoctta/multiple-attention are: Detection Models.
Projects with overlapping indexed features include: cfeng16/audio-visual-forensics — Self-Supervised Video Forensics by Audio-Visual Anomaly Detection Chao Feng, Ziyang Chen, Andrew Owens University of… chuangchuangtan/lgrad — Beijing Jiaotong University, YanShan University. chuangchuangtan/npr-deepfakedetection — Beijing Jiaotong University, YanShan University, A*Star. crywang/rfm — This repository contains the Pytorch implementation of Representative Forgery Mining for Fake Face Detection. If you… frederickszk/lrnet — Landmark Recurrent Network: An efficient and robust framwork for Deepfakes detection. 10ring/laa-net — This is an official implementation for LAA-Net! [Paper].
