MANUS: Markerless Grasp Capture using Articulated 3D Gaussians

arXiv:2312.02137v2 Announce Type: replace
Abstract: Understanding how we grasp objects with our hands has important applications in areas like robotics and mixed reality. However, this challenging problem requires accurate modeling of the contact between hands and objects. To capture grasps, existing methods use skeletons, meshes, or parametric models that does not represent hand shape accurately resulting in inaccurate contacts. We present MANUS, a method for Markerless Hand-Object Grasp Capture using Articulated 3D Gaussians. We build a novel articulated 3D Gaussians …

abstract applications arxiv cs.cv however meshes mixed mixed reality modeling objects parametric reality robotics type understanding