6 papers
Text2Interact: High-Fidelity and Diverse Text-to-Two-Person Interaction Generation
Qingxuan Wu, Zhiyang Dou, Chuan Guo +5
Modeling human-human interactions from text remains challenging because it requires not only realistic individual dynamics but also precise, text-consistent spatiotemporal coupling…
PhysHMR: Learning Humanoid Control Policies from Vision for Physically Plausible Human Motion Reconstruction
Qiao Feng, Yiming Huang, Yufu Wang +2
Reconstructing physically plausible human motion from monocular videos remains a challenging problem in computer vision and graphics. Existing methods primarily focus on kinematics…
PhysCtrl: Generative Physics for Controllable and Physics-Grounded Video Generation
Chen Wang, Chuhao Chen, Yiming Huang +4
Existing video generation models excel at producing photo-realistic videos from text or images, but often lack physical plausibility and 3D controllability. To overcome these limit…
FormCoach: Lift Smarter, Not Harder
Xiaoye Zuo, Nikos Athanasiou, Ginger Delmas +3
Good form is the difference between strength and strain, yet for the fast-growing community of at-home fitness enthusiasts, expert feedback is often out of reach. FormCoach transfo…
Vid2Sim: Generalizable, Video-based Reconstruction of Appearance, Geometry and Physics for Mesh-free Simulation
Chuhao Chen, Zhiyang Dou, Chen Wang +5
Faithfully reconstructing textured shapes and physical properties from videos presents an intriguing yet challenging problem. Significant efforts have been dedicated to advancing s…
ModSkill: Physical Character Skill Modularization
Yiming Huang, Zhiyang Dou, Lingjie Liu
Human motion is highly diverse and dynamic, posing challenges for imitation learning algorithms that aim to generalize motor skills for controlling simulated characters. Previous m…