20 citations · 179 across the 97 of their papers we have counts for
12 papers · 2 filters
Transcending Forgery Specificity with Latent Space Augmentation for Generalizable Deepfake Detection
Zhiyuan Yan, Yuhao Luo, Siwei Lyu +2
Deepfake detection faces a critical generalization hurdle, with performance deteriorating when there is a mismatch between the distributions of training and testing data. A broadly…
Integrating Audio-Visual Features for Multimodal Deepfake Detection
Sneha Muppalla, Shan Jia, Siwei Lyu
Deepfakes are AI-generated media in which an image or video has been digitally modified. The advancements made in deepfake technology have led to privacy and security issues. Most…
CrossDF: Improving Cross-Domain Deepfake Detection with Deep Information Decomposition
Shanmin Yang, Hui Guo, Shu Hu +5
Deepfake technology poses a significant threat to security and social trust. Although existing detection methods have shown high performance in identifying forgeries within dataset…
Controlling Neural Style Transfer with Deep Reinforcement Learning
Chengming Feng, Jing Hu, Xin Wang +5
Controlling the degree of stylization in the Neural Style Transfer (NST) is a little tricky since it usually needs hand-engineering on hyper-parameters. In this paper, we propose t…
Language-guided Human Motion Synthesis with Atomic Actions
Yuanhao Zhai, Mingzhen Huang, Tianyu Luan +5
Language-guided human motion synthesis has been a challenging task due to the inherent complexity and diversity of human behaviors. Previous methods face limitations in generalizat…
COMICS: End-to-end Bi-grained Contrastive Learning for Multi-face Forgery Detection
Cong Zhang, Honggang Qi, Shuhui Wang +2
DeepFakes have raised serious societal concerns, leading to a great surge in detection-based forensics methods in recent years. Face forgery recognition is a standard detection met…
ForensicsForest Family: A Series of Multi-scale Hierarchical Cascade Forests for Detecting GAN-generated Faces
Jiucui Lu, Jiaran Zhou, Junyu Dong +3
The prominent progress in generative models has significantly improved the reality of generated faces, bringing serious concerns to society. Since recent GAN-generated faces are in…
FakeTracer: Catching Face-swap DeepFakes via Implanting Traces in Training
Pu Sun, Honggang Qi, Yuezun Li +1
Face-swap DeepFake is an emerging AI-based face forgery technique that can replace the original face in a video with a generated face of the target identity while retaining consist…
DeepfakeBench: A Comprehensive Benchmark of Deepfake Detection
Zhiyuan Yan, Yong Zhang, Xinhang Yuan +2
A critical yet frequently overlooked challenge in the field of deepfake detection is the lack of a standardized, unified, comprehensive benchmark. This issue leads to unfair perfor…
Improving Fairness in Deepfake Detection
Yan Ju, Shu Hu, Shan Jia +2
Despite the development of effective deepfake detectors in recent years, recent studies have demonstrated that biases in the data used to train these detectors can lead to disparit…
AutoSplice: A Text-prompt Manipulated Image Dataset for Media Forensics
Shan Jia, Mingzhen Huang, Zhou Zhou +3
Recent advancements in language-image models have led to the development of highly realistic images that can be generated from textual descriptions. However, the increased visual q…
Attacking Important Pixels for Anchor-free Detectors
Yunxu Xie, Shu Hu, Xin Wang +4
Deep neural networks have been demonstrated to be vulnerable to adversarial attacks: subtle perturbation can completely change the prediction result. Existing adversarial attacks o…