1 citations · 1 across the 4 of their papers we have counts for
4 papers
TRiMM: Transformer-Based Rich Motion Matching for Real-Time multi-modal Interaction in Digital Humans
Yueqian Guo, Tianzhao Li, Xin Lyu +7
Large Language Model (LLM)-driven digital humans have sparked a series of recent studies on co-speech gesture generation systems. However, existing approaches struggle with real-ti…
DiM-Gestor: Co-Speech Gesture Generation with Adaptive Layer Normalization Mamba-2
Fan Zhang, Siyuan Zhao, Naye Ji +12
Speech-driven gesture generation using transformer-based generative models represents a rapidly advancing area within virtual human creation. However, existing models face signific…
Speech-driven Personalized Gesture Synthetics: Harnessing Automatic Fuzzy Feature Inference
Fan Zhang, Zhaohan Wang, Xin Lyu +8
Speech-driven gesture generation is an emerging field within virtual human creation. However, a significant challenge lies in accurately determining and processing the multitude of…
Audio is all in one: speech-driven gesture synthetics using WavLM pre-trained model
Fan Zhang, Naye Ji, Fuxing Gao +3
The generation of co-speech gestures for digital humans is an emerging area in the field of virtual human creation. Prior research has made progress by using acoustic and semantic…