Masked relation learning for deepfake detection
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 …
formulate it as a binary classification problem by solely mining the local artifacts and …
Styleswap: Style-based generator empowers robust face swapping
Numerous attempts have been made to the task of person-agnostic face swapping given its
wide applications. While existing methods mostly rely on tedious network and loss designs …
wide applications. While existing methods mostly rely on tedious network and loss designs …
Deepfake Detection: A Comprehensive Survey from the Reliability Perspective
The mushroomed Deepfake synthetic materials circulated on the internet have raised a
profound social impact on politicians, celebrities, and individuals worldwide. In this survey …
profound social impact on politicians, celebrities, and individuals worldwide. In this survey …
Beyond the prior forgery knowledge: Mining critical clues for general face forgery detection
Face forgery detection is essential in combating malicious digital face attacks. Previous
methods mainly rely on prior expert knowledge to capture specific forgery clues, such as …
methods mainly rely on prior expert knowledge to capture specific forgery clues, such as …
Revisiting generalizability in deepfake detection: Improving metrics and stabilizing transfer
Abstract" Generalizability" is seen as the hallmark quality of a good deepfake detection
model. However, standard out-of-domain evaluation datasets are very similar in form to the …
model. However, standard out-of-domain evaluation datasets are very similar in form to the …
MSVT: Multiple spatiotemporal views transformer for DeepFake video detection
Recently, DeepFake videos have developed rapidly, causing new security issues in society.
Due to the rough spatiotemporal view, existing video-based detection methods struggle to …
Due to the rough spatiotemporal view, existing video-based detection methods struggle to …
Locate and verify: A two-stream network for improved deepfake detection
Deepfake has taken the world by storm, triggering a trust crisis. Current deepfake detection
methods are typically inadequate in generalizability, with a tendency to overfit to image …
methods are typically inadequate in generalizability, with a tendency to overfit to image …
Unified frequency-assisted transformer framework for detecting and grounding multi-modal manipulation
Detecting and grounding multi-modal media manipulation (DGM 4) has become
increasingly crucial due to the widespread dissemination of face forgery and text …
increasingly crucial due to the widespread dissemination of face forgery and text …
Fake it till you make it: Curricular dynamic forgery augmentations towards general deepfake detection
Previous studies in deepfake detection have shown promising results when testing face
forgeries from the same dataset as the training. However, the problem remains challenging …
forgeries from the same dataset as the training. However, the problem remains challenging …
Moe-ffd: Mixture of experts for generalized and parameter-efficient face forgery detection
Deepfakes have recently raised significant trust issues and security concerns among the
public. Compared to CNN face forgery detectors, ViT-based methods take advantage of the …
public. Compared to CNN face forgery detectors, ViT-based methods take advantage of the …