Othmane Harraq, Tamer Aldwairi
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Talking-face (TF) deepfakes are detected unevenly by rPPG-based methods across generators. We study two lightweight visual-only cues, rPPG-derived waveforms extracted by RhythmFormer and lip-region discrete cosine transform (DCT) coefficients, on the seven TF methods of Celeb-DF++ under a subject-independent protocol. In-domain, lip-region DCT matches or exceeds the rPPG-derived 1D ResNet on every method except SadTalker, and Concat fusion reaches AUC 0.891 against 0.824 and 0.827 for the unimodal baselines. Under leave-one-generator-out evaluation the cues split: each transfers clearly better to three held-out methods, and IP-LAP is near chance for both. Concat averages 0.798 but falls below rPPG alone where DCT transfers poorly, so static fusion only partly exploits this complementarity. Lip-region DCT outperforms full-face DCT on six of seven methods. We treat the rPPG-derived signal as an empirical cue and do not claim it is cardiac in origin.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2609.22284")
get_code_for_paper("2609.22284")
have("2609.22284")
The run record, dated, one paper per request, free:
curl https://syntology.ai/api/ran/2609.22284.json
A badge for a README (the split and the date, never a ratio):
[](https://syntology.ai/paper/2609.22284)
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