42 citations · 198 across the 27 of their papers we have counts for
5 papers · 1 filter
CHORD: Category-level Hand-held Object Reconstruction via Shape Deformation
Kailin Li, Lixin Yang, Haoyu Zhen +6
In daily life, humans utilize hands to manipulate objects. Modeling the shape of objects that are manipulated by the hand is essential for AI to comprehend daily tasks and to learn…
Color-NeuS: Reconstructing Neural Implicit Surfaces with Color
Licheng Zhong, Lixin Yang, Kailin Li +3
The reconstruction of object surfaces from multi-view images or monocular video is a fundamental issue in computer vision. However, much of the recent research concentrates on reco…
POEM: Reconstructing Hand in a Point Embedded Multi-view Stereo
Lixin Yang, Jian Xu, Licheng Zhong +4
Enable neural networks to capture 3D geometrical-aware features is essential in multi-view based vision tasks. Previous methods usually encode the 3D information of multi-view ster…
NIKI: Neural Inverse Kinematics with Invertible Neural Networks for 3D Human Pose and Shape Estimation
Jiefeng Li, Siyuan Bian, Qi Liu +3
With the progress of 3D human pose and shape estimation, state-of-the-art methods can either be robust to occlusions or obtain pixel-aligned accuracy in non-occlusion cases. Howeve…
HybrIK-X: Hybrid Analytical-Neural Inverse Kinematics for Whole-body Mesh Recovery
Jiefeng Li, Siyuan Bian, Chao Xu +3
Recovering whole-body mesh by inferring the abstract pose and shape parameters from visual content can obtain 3D bodies with realistic structures. However, the inferring process is…