defense arXiv Jan 2, 2026 · Jan 2026
Shukesh Reddy, Srijan Das, Abhijit Das · Birla Institute of Technology and Science · University of North Carolina at Charlotte
Novel deepfake detector fusing self-supervised auxiliary task features with primary encoder to improve cross-dataset generalization across face forgery benchmarks
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In this work, we attempted to unleash the potential of self-supervised learning as an auxiliary task that can optimise the primary task of generalised deepfake detection. To explore this, we examined different combinations of the training schemes for these tasks that can be most effective. Our findings reveal that fusing the feature representation from self-supervised auxiliary tasks is a powerful feature representation for the problem at hand. Such a representation can leverage the ultimate potential and bring in a unique representation of both the self-supervised and primary tasks, achieving better performance for the primary task. We experimented on a large set of datasets, which includes DF40, FaceForensics++, Celeb-DF, DFD, FaceShifter, UADFV, and our results showed better generalizability on cross-dataset evaluation when compared with current state-of-the-art detectors.
cnn transformer Birla Institute of Technology and Science · University of North Carolina at Charlotte
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