12 papers
ScaleMoGen: Autoregressive Next-Scale Prediction for Human Motion Generation
Inwoo Hwang, Hojun Jang, Bing Zhou +3
We present ScaleMoGen, a scale-wise autoregressive framework for text-driven human motion generation. Unlike conventional autoregressive approaches that rely on standard next-token…
SpaceDex: Generalizable Dexterous Grasping in Tiered Workspaces
Wensheng Wang, Chuanjun Guo, Wei Wei +2
Generalizable grasping with high-degree-of-freedom (DoF) dexterous hands remains challenging in tiered workspaces, where occlusion, narrow clearances, and height-dependent constrai…
HandX: Scaling Bimanual Motion and Interaction Generation
Zimu Zhang, Yucheng Zhang, Xiyan Xu +8
Synthesizing human motion has advanced rapidly, yet realistic hand motion and bimanual interaction remain underexplored. Whole-body models often miss the fine-grained cues that dri…
Unleashing Guidance Without Classifiers for Human-Object Interaction Animation
Ziyin Wang, Sirui Xu, Chuan Guo +5
Generating realistic human-object interaction (HOI) animations remains challenging because it requires jointly modeling dynamic human actions and diverse object geometries. Prior d…
AHA! Animating Human Avatars in Diverse Scenes with Gaussian Splatting
Aymen Mir, Jian Wang, Riza Alp Guler +3
We present a novel framework for animating humans in 3D scenes using 3D Gaussian Splatting (3DGS), a neural scene representation that has recently achieved state-of-the-art photore…
SnapMoGen: Human Motion Generation from Expressive Texts
Chuan Guo, Inwoo Hwang, Jian Wang +1
Text-to-motion generation has experienced remarkable progress in recent years. However, current approaches remain limited to synthesizing motion from short or general text prompts,…