arXiv:2505.12296v2 Announce Type: replace-cross
Abstract: Our evaluation shows that PoLO achieves textbf99% watermark detection accuracy for ownership verification, while preserving data privacy and cutting verification costs to just textbf1.5–10% of traditional methods. Forging PoLO demands textbf1.1–4$times$ more resources than honest proof generation, with the original proof retaining over textbf90% detection accuracy even after attacks.
EAD-Net: Emotion-Aware Talking Head Generation with Spatial Refinement and Temporal Coherence
arXiv:2604.23325v1 Announce Type: cross Abstract: Emotionally talking head video generation aims to generate expressive portrait videos with accurate lip synchronization and emotional facial expressions. Current


