Media Forensic Considerations of the Usage of Artificial Intelligence Using the Example of DeepFake Detection. [PDF]
Siegel D +3 more
europepmc +1 more source
Dual-domain self-supervised feature alignment via spectral-spatial representation learning for deepfake anomaly detection. [PDF]
He Y.
europepmc +1 more source
Deepfakebuster: a confidence-calibrated adaptive ensemble framework for robust Deepfake image detection. [PDF]
Patil R +4 more
europepmc +1 more source
Bioinspired Adaptive-Depth Neural Growth for Deepfake Video Forensics: An Entropy-Guided State-Space Framework. [PDF]
Hussain M, Saeed F, Aldera S.
europepmc +1 more source
DeepFake-Adapter: Dual-Level Adapter for DeepFake Detection
Existing deepfake detection methods fail to generalize well to unseen or degraded samples, which can be attributed to the over-fitting of low-level forgery patterns. Here we argue that high-level semantics are also indispensable recipes for generalizable
Ziwei Liu, Rui Shao, Liqiang Nie
exaly +3 more sources
Deepfake video detection: challenges and opportunities [PDF]
Deepfake videos are a growing social issue. These videos are manipulated by artificial intelligence (AI) techniques (especially deep learning), an emerging societal issue.
Feng Xia, Selena
exaly +2 more sources
Deepfake Detection Using Spatiotemporal Transformer [PDF]
International audienceRecent advances in generative models and the availability of large-scale benchmarks have made deepfake video generation and manipulation easier.
Sid Ahmed FEZZA +2 more
exaly +2 more sources
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