3 citations · 5 across the 16 of their papers we have counts for
6 papers · 1 filter
InterMimicGen: Scaling Humanoid Loco-Manipulation through Self-Evolving Motion Imitation
Yucheng Zhang, Sirui Xu, Jinhong Li +8
Captured human-object interactions provide rich supervision for humanoid loco-manipulation, but they are sparse, heterogeneous, and not directly executable by robots. We introduce…
DETRAM: End-to-end DEtection, Tracking and Recovery of HumAn Meshes
Chunggi Lee, Seonwook Park, Wanhua Li +2
In the task of human mesh recovery (HMR), multi-person scenes are particularly difficult to handle due to the many entities that appear and occlusions between them over time. In pa…
GRAIL: Generating Humanoid Loco-Manipulation from World Models
Tianyi Xie, Haotian Zhang, Jinhyung Park +17
Scaling humanoid loco-manipulation requires robot-compatible demonstrations across diverse objects, whole-body motions, and scene geometries, but teleoperation and motion capture a…
D-Rex : Diffusion Rendering for Relightable Expressive Avatars
Timo Teufel, Xilong Zhou, Umar Iqbal +4
We present D-Rex, a person-specific framework for photorealistic, relightable, expressive, and animatable full-body human avatars with free-viewpoint rendering. Existing methods fo…
SOMA: Unifying Parametric Human Body Models
Jun Saito, Jiefeng Li, Michael de Ruyter +12
Parametric human body models are foundational to human reconstruction, animation, and simulation, yet they remain mutually incompatible: SMPL, SMPL-X, MHR, Anny, and related models…
Kimodo: Scaling Controllable Human Motion Generation
Davis Rempe, Mathis Petrovich, Ye Yuan +21
High-quality human motion data is becoming increasingly important for applications in robotics, simulation, and entertainment. Recent generative models offer a potential data sourc…