5 papers
Bridging Semantic and Kinematic Conditions with Diffusion-based Discrete Motion Tokenizer
Chenyang Gu, Mingyuan Zhang, Haozhe Xie +3
Prior motion generation largely follows two paradigms: continuous diffusion models that excel at kinematic control, and discrete token-based generators that are effective for seman…
InfiniteDance: Scalable 3D Dance Generation Towards in-the-wild Generalization
Ronghui Li, Zhongyuan Hu, Li Siyao +6
Although existing 3D dance generation methods perform well in controlled scenarios, they often struggle to generalize in the wild. When conditioned on unseen music, existing method…
CrowdMoGen: Zero-Shot Text-Driven Collective Motion Generation
Yukang Cao, Xinying Guo, Mingyuan Zhang +3
While recent advances in text-to-motion generation have shown promising results, they typically assume all individuals are grouped as a single unit. Scaling these methods to handle…
SMPLest-X: Ultimate Scaling for Expressive Human Pose and Shape Estimation
Wanqi Yin, Zhongang Cai, Ruisi Wang +12
Expressive human pose and shape estimation (EHPS) unifies body, hands, and face motion capture with numerous applications. Despite encouraging progress, current state-of-the-art me…
RMD: A Simple Baseline for More General Human Motion Generation via Training-free Retrieval-Augmented Motion Diffuse
Zhouyingcheng Liao, Mingyuan Zhang, Wenjia Wang +2
While motion generation has made substantial progress, its practical application remains constrained by dataset diversity and scale, limiting its ability to handle out-of-distribut…