7 citations · 12 across the 7 of their papers we have counts for
6 papers · 1 filter
World2Motion: Turning Video World Models into 3D Human Motion Generators
Fangyuan Tu, Tu Fangyuan, Xiangyue Zhang +9
We present World2Motion, a framework that generates scene-aware 3D human motion and corresponding video from a single image and a text prompt. While existing 3D motion generators l…
StreamTalk: Streaming Co-Speech Gesture Generation with Key-Pose Anchoring
Xiangyue Zhang, Jianfang Li, Jiaxu Zhang +2
Real-time co-speech gesture generation must produce 3D motion clip by clip as speech arrives. Existing streaming methods are open-loop: each clip depends on past context, but the m…
PersonaGesture: Single-Reference Co-Speech Gesture Personalization for Unseen Speakers
Xiangyue Zhang, Yiyi Cai, Kunhang Li +6
We propose PersonaGesture, a diffusion-based pipeline for single-reference co-speech gesture personalization of unseen speakers. Given target speech and one motion clip from a new…
Not All Frames Are Equal: Complexity-Aware Masked Motion Generation via Motion Spectral Descriptors
Pengfei Zhou, Xiangyue Zhang, Xukun Shen +1
Masked generative models have become a strong paradigm for text-to-motion synthesis, but they still treat motion frames too uniformly during masking, attention, and decoding. This…
Mitigating Error Accumulation in Co-Speech Motion Generation via Global Rotation Diffusion and Multi-Level Constraints
Xiangyue Zhang, Jianfang Li, Jianqiang Ren +1
Reliable long-horizon co-speech gesture generation requires precise motion representation and consistent structural priors across all joints. Existing generative methods typically…
SemTalk: Holistic Co-speech Motion Generation with Frame-level Semantic Emphasis
Xiangyue Zhang, Jianfang Li, Jiaxu Zhang +4
Co-speech gesture generation must carefully integrate common rhythmic motion with rare yet essential semantic gestures. In this work, we propose SemTalk for holistic co-speech gest…