DynamicHOI: Coupled Dynamics for Physics-aware HOI Reconstruction
Read the original on arXiv Computer Vision →The Flow has not summarised this story yet — read it at arXiv Computer Vision.
The Flow has not summarised this story yet — read it at arXiv Computer Vision.
arXiv:2609.19119v1 Announce Type: new Abstract: Human videos contain rich causal evidence for robot manipulation: they reveal how hand motion induces object motion and produces task-relevant changes...
Grasp in Gaussians (GraG) is a fast, robust method for reconstructing dynamic 3D hand‑object interactions from a single monocular video. It leverages pretrained hand and object priors and represents the scene with a compact Sum‑of‑Gaussians (SoG) model, enabling efficient tracking while preserving geometric fidelity. Experiments show GraG achieves temporally coherent reconstructions on long sequences 4.4×–38.9× faster than prior work.
arXiv:2608.13014v2 Announce Type: replace Abstract: Understanding hand-object interaction from egocentric vision is essential for modeling how people physically engage with the surrounding world. Yet...
Text driven hand object interaction (HOI) generation is gaining attention for immersive applications and robotics, yet producing physically plausible interactions remains challenging. Even when individual motions appear natural, small contact errors can cause conspicuous artifacts such as floating and interpenetration.
arXiv:2608.28386v1 Announce Type: new Abstract: Existing monocular full-body 3D human-object interaction (HOI) methods do not combine explicit finger-level grasp optimization with category-agnostic o...
arXiv:2505. 05517v3 Announce Type: replace-cross Abstract: Functional grasping is essential for enabling dexterous multi-finger robot hands to manipulate objects effectively.