EAD-Net uses a diffusion model with new spatio-temporal attention, graph-based temporal reasoning, and LLM-derived semantic descriptions to generate emotionally expressive talking head videos with improved lip-sync and coherence over prior methods.
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PianoFlow generates coordinated bimanual piano motions from audio via MIDI-distilled flow-matching, asymmetric role-gated interaction, and autoregressive streaming continuation, outperforming priors with 9x faster inference.
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EAD-Net: Emotion-Aware Talking Head Generation with Spatial Refinement and Temporal Coherence
EAD-Net uses a diffusion model with new spatio-temporal attention, graph-based temporal reasoning, and LLM-derived semantic descriptions to generate emotionally expressive talking head videos with improved lip-sync and coherence over prior methods.
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PianoFlow: Music-Aware Streaming Piano Motion Generation with Bimanual Coordination
PianoFlow generates coordinated bimanual piano motions from audio via MIDI-distilled flow-matching, asymmetric role-gated interaction, and autoregressive streaming continuation, outperforming priors with 9x faster inference.