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Erwin Wu

2 accepted papers

2026

DyaDiT: A Multi-Modal Diffusion Transformer for Socially Favorable Dyadic Gesture Generation

CVPR 2026

Generating realistic conversational gestures are essential for achieving natural, socially engaging interactions with digital humans. However, existing methods typically map a single audio stream to a single speaker's motion, without considering social context or modeling the mutual dynamics between

Cited by 0SourceScholar
2025

From Pose to Muscle: Multimodal Learning for Piano Hand Muscle Electromyography

NeurIPS 2025poster

Muscle coordination is fundamental when humans interact with the world. Reliable estimation of hand muscle engagement can serve as a source of internal feedback, supporting the development of embodied intelligence and the acquisition of dexterous skills. However, contemporary electromyography (EMG)…

Cited by 0SourceScholar