![]() ![]() An ablation study is performed to investigate the effect of the different components and style transfer losses. Evaluations on various deep fake benchmarks (DFTIMIT, UADFV, Celeb-DF, and FaceForensics++) show that the proposed method achieves the best overall performance. This addition ensures that the learned features are shared by multiple domains and provides better generalization abilities to unseen deep fake samples. The center and triplet losses are added to enhance generalization. To this end, the maximum mean discrepancy (MMD) loss is incorporated to align the different feature distributions. DeviantArt is the worlds largest online social community for artists and art. ![]() ![]() Furthermore, artifacts such as imaging variations or face attributes do not persistently exist among all generated results for a single generation method.Therefore, in this paper, we propose a novel framework to address the domain gap induced by multiple deep fake datasets. MMD Parts - Face - Male TDA Face edit by ColorsOfOrion on DeviantArt. The main drawback of existing face forensics detection methods is their limited generalization ability due to differences in domains. Face forensic detection is to distinguish manipulated from pristine face images. ![]()
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