570 citations · 699 across the 24 of their papers we have counts for
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Cascaded Refinement Network for Point Cloud Completion with Self-supervision
Xiaogang Wang, Marcelo H Ang, Gim Hee Lee
Point clouds are often sparse and incomplete, which imposes difficulties for real-world applications. Existing shape completion methods tend to generate rough shapes without fine-g…
Point Cloud Completion by Learning Shape Priors
Xiaogang Wang, Marcelo H Ang, Gim Hee Lee
In view of the difficulty in reconstructing object details in point cloud completion, we propose a shape prior learning method for object completion. The shape priors include geome…
Shape Prior Deformation for Categorical 6D Object Pose and Size Estimation
Meng Tian, Marcelo H Ang, Gim Hee Lee
We present a novel learning approach to recover the 6D poses and sizes of unseen object instances from an RGB-D image. To handle the intra-class shape variation, we propose a deep…
Toward Hierarchical Self-Supervised Monocular Absolute Depth Estimation for Autonomous Driving Applications
Feng Xue, Guirong Zhuo, Ziyuan Huang +3
In recent years, self-supervised methods for monocular depth estimation has rapidly become an significant branch of depth estimation task, especially for autonomous driving applica…
Cascaded Refinement Network for Point Cloud Completion
Xiaogang Wang, Marcelo H Ang, Gim Hee Lee
Point clouds are often sparse and incomplete. Existing shape completion methods are incapable of generating details of objects or learning the complex point distributions. To this…
Robust 6D Object Pose Estimation by Learning RGB-D Features
Meng Tian, Liang Pan, Marcelo H Ang +1
Accurate 6D object pose estimation is fundamental to robotic manipulation and grasping. Previous methods follow a local optimization approach which minimizes the distance between c…