Artifacts-Disentangled Adversarial Learning for Deepfake Detection
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2022.3217950
Abstract: Due to the development of facial manipulation technologies, the generated deepfake videos cause a severe trust crisis in society. Existing methods prove that effective extraction of the artifacts introduced during the forgery process is essential… read more here.
Keywords: artifacts disentangled; detection; adversarial learning; disentangled adversarial ... See more keywords
Masked Relation Learning for DeepFake Detection
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Information Forensics and Security"
DOI: 10.1109/tifs.2023.3249566
Abstract: DeepFake detection aims to differentiate falsified faces from real ones. Most approaches formulate it as a binary classification problem by solely mining the local artifacts and inconsistencies of face forgery, which neglect the relation across… read more here.
Keywords: masked relation; relation learning; learning deepfake; deepfake detection ... See more keywords