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20192021
most citedDisentangling Pose from Appearance in Monochrome Hand Images

2 citations · 4 across the 2 of their papers we have counts for

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cs.CV20212 cited

Identity-Disentangled Neural Deformation Model for Dynamic Meshes

Binbin Xu, Lingni Ma, Yuting Ye +3

Neural shape models can represent complex 3D shapes with a compact latent space. When applied to dynamically deforming shapes such as the human hands, however, they would need to p…

cs.CV2021

ContactOpt: Optimizing Contact to Improve Grasps

Patrick Grady, Chengcheng Tang, Christopher D. Twigg +3

Physical contact between hands and objects plays a critical role in human grasps. We show that optimizing the pose of a hand to achieve expected contact with an object can improve…

cs.CV2020

UNOC: Understanding Occlusion for Embodied Presence in Virtual Reality

Mathias Parger, Chengcheng Tang, Yuanlu Xu +5

Tracking body and hand motions in the 3D space is essential for social and self-presence in augmented and virtual environments. Unlike the popular 3D pose estimation setting, the p…

cs.CV2020

ContactPose: A Dataset of Grasps with Object Contact and Hand Pose

Samarth Brahmbhatt, Chengcheng Tang, Christopher D. Twigg +2

Grasping is natural for humans. However, it involves complex hand configurations and soft tissue deformation that can result in complicated regions of contact between the hand and…

cs.CV20192 cited

Disentangling Pose from Appearance in Monochrome Hand Images

Yikang Li, Chris Twigg, Yuting Ye +2

Hand pose estimation from the monocular 2D image is challenging due to the variation in lighting, appearance, and background. While some success has been achieved using deep neural…