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Improving Generalization by Commonality Learning in Face Forgery Detection
IEEE Transactions on Information Forensics and Security, 2022Peipeng Yu, Jianwei Fei, Zhihua Xia
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Visual-Semantic Transformer for Face Forgery Detection
2021 IEEE International Joint Conference on Biometrics (IJCB), 2021This paper proposes a novel Visual-Semantic Transformer (VST) to detect face forgery based on semantic aware feature relations. In face images, intrinsic feature relations exist between different semantic parsing regions. We find that face forgery algorithms always change such relations. Therefore, we start the approach by extracting Contextual Feature
Yuting Xu +4 more
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A survey on face forgery detection of Deepfake
Thirteenth International Conference on Digital Image Processing (ICDIP 2021), 2021With the development of internet technology, artificial intelligence shows its rapid growth in recent year as well. More and more people pay attention to this field, including criminals inevitably. It is noted that one technology called “Deepfake” appeared on the internet at the end of 2017.
Ying Zhang +3 more
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An Overview of Face Image Forgery Detection
Current Chinese Computer Science, 2022: With the development of face forgery techniques, the spread and malicious abuse of forged images have become a thought-provoking problem, and the face forgery detection technique has also attracted people's attention. Academia has carried out in-depth research and discussion on detection techniques.
Defen He +4 more
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Forgery-Aware Adaptive Learning With Vision Transformer for Generalized Face Forgery Detection
IEEE Transactions on Circuits and Systems for Video TechnologyAnwei Luo, Rizhao Cai, Chenqi Kong
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MMD Based Discriminative Learning for Face Forgery Detection
2021Face forensic detection is to distinguish manipulated from pristine face images. The main drawback of existing face forensics detection methods is their limited generalization ability due to differences in domains. Furthermore, artifacts such as imaging variations or face attributes do not persistently exist among all generated results for a single ...
Jian Han, Theo Gevers
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Face Forgery Detection Based On Segmentation Network
2021 IEEE International Conference on Image Processing (ICIP), 2021Yingbin Zhou +3 more
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A review of human face forgery and forgery-detection technologies
Journal of Image and Graphics, 2022Cao Shenhao +3 more
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Face Forgery Detection via Symmetric Transformer
Proceedings of the 30th ACM International Conference on Multimedia, 2022Luchuan Song +5 more
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Multi-attention Based Face Forgery Detection
2023 4th International Conference on Computer Engineering and Intelligent Control (ICCEIC), 2023Xiang Han +4 more
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