5 papers
Motion Style Slider: Endpoint-Supervised Continuous Style Control for Human Motion Diffusion
Chen-Chieh Liao, Yichen Peng, Yiyi Cai +5
Existing human motion diffusion methods provide strong motion generation quality, and recent style transfer models can inject target style cues, but fine-grained continuous control…
InterPet4D: A Multimodal 4D Human-Pet Interaction Dataset for Pet Motion Generation
Yichen Peng, Jyun-Ting Song, Chen-Chieh Liao +3
Human-pet interaction estimation and generation remain underexplored due to the absence of a high-quality large-scale dataset. We present InterPet4D, the first multimodal dataset c…
DyaDiT: A Multi-Modal Diffusion Transformer for Socially Favorable Dyadic Gesture Generation
Yichen Peng, Jyun-Ting Song, Siyeol Jung +7
Generating realistic conversational gestures are essential for achieving natural, socially engaging interactions with digital humans. However, existing methods typically map a sing…
Sensing Your Vocals: Exploring the Activity of Vocal Cord Muscles for Pitch Assessment Using Electromyography and Ultrasonography
Kanyu Chen, Rebecca Panskus, Erwin Wu +9
Vocal training is difficult because the muscles that control pitch, resonance, and phonation are internal and invisible to learners. This paper investigates how Electromyography (E…
SimDiff: Simulator-constrained Diffusion Model for Physically Plausible Motion Generation
Akihisa Watanabe, Jiawei Ren, Li Siyao +3
Generating physically plausible human motion is crucial for applications such as character animation and virtual reality. Existing approaches often incorporate a simulator-based mo…