activity
20172023
most citedLearning Object Bounding Boxes for 3D Instance Segmentation on Point Clouds

262 citations · 1.1k across the 28 of their papers we have counts for

collaborators
Showing 2020Show all

9 papers · 1 filter

cs.RO2020

Natural grasp intention recognition based on gaze fixation in human-robot interaction

Bo Yang, Jian Huang, Xiaolong Li +3

Eye movement is closely related to limb actions, so it can be used to infer movement intentions. More importantly, in some cases, eye movement is the only way for paralyzed and imp…

cs.CV2020★ 5 cited

Graph and Temporal Convolutional Networks for 3D Multi-person Pose Estimation in Monocular Videos

Yu Cheng, Bo Wang, Bo Yang +1

Despite the recent progress, 3D multi-person pose estimation from monocular videos is still challenging due to the commonly encountered problem of missing information caused by occ…

cs.CV2020★ 15 cited

SpinNet: Learning a General Surface Descriptor for 3D Point Cloud Registration

Sheng Ao, Qingyong Hu, Bo Yang +2

Extracting robust and general 3D local features is key to downstream tasks such as point cloud registration and reconstruction. Existing learning-based local descriptors are either…

cs.CV2020

Learning to Reconstruct and Segment 3D Objects

Bo Yang

To endow machines with the ability to perceive the real-world in a three dimensional representation as we do as humans is a fundamental and long-standing topic in Artificial Intell…

cs.CV2020★ 2 cited

Multi-Scale Networks for 3D Human Pose Estimation with Inference Stage Optimization

Cheng Yu, Bo Wang, Bo Yang +1

Estimating 3D human poses from a monocular video is still a challenging task. Many existing methods' performance drops when the target person is occluded by other objects, or the m…

cs.CV2020★ 1 cited

GRF: Learning a General Radiance Field for 3D Representation and Rendering

Alex Trevithick, Bo Yang

We present a simple yet powerful neural network that implicitly represents and renders 3D objects and scenes only from 2D observations. The network models 3D geometries as a genera…