3d-motion

HarmoHOI is a unified diffusion framework that jointly generates synchronized multi-view hand-object interaction videos and globally aligned 3D point tracks, achieving state-of-the-art performance in visual quality, motion plausibility, and multi-view geometric consistency.

AFUN proposes an affordance foundation model that predicts functional masks and 3D motion curves from RGB-D observations and language descriptions, enabling generalizable robot manipulation across diverse environments. The model outperforms baselines on multiple benchmarks and can be deployed for real-world tasks without fine-tuning.

PhyMotion proposes a physics-grounded reward system that evaluates kinematic plausibility, contact consistency, and dynamic feasibility of human motion in generated videos, achieving stronger correlation with human judgment and improving motion realism in RL-based post-training.