An audio-visual deepfake detector combining adaptive contrastive learning, multi-scale fusion, and orthogonalized Pareto gradient balancing reports state-of-the-art accuracy (95.5% average) and strong cross-dataset transfer on three benchmarks.
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Multiscale Adaptive Conflict-Balancing Model For Multimedia Deepfake Detection
An audio-visual deepfake detector combining adaptive contrastive learning, multi-scale fusion, and orthogonalized Pareto gradient balancing reports state-of-the-art accuracy (95.5% average) and strong cross-dataset transfer on three benchmarks.