InfoResearchPeer-reviewed
Dual-Tree Complex Wavelet Driven Hierarchical Spatial-Frequency Fusion Learning for Robust Deepfake Detection
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Summary
Researchers address deepfake detection, where high-fidelity generators remove explicit traces and leave only subtle frequency-domain artifacts. They propose a Hierarchical Spatial-Frequency Fusion (HSFF) module with frequency attention, paired with a Collaborative Multi-Subband Enhancement (CMSE) mechanism that combines Dual-Tree Complex Wavelet Transform (DTCWT) features with pre-trained visual features across six directional subbands. The method reports 97.2% cross-dataset AUROC on Celeb-DFv2 and 89.1% on DFDC.