17 citations · 51 across the 29 of their papers we have counts for
5 papers · 1 filter
3D Hierarchical Refinement and Augmentation for Unsupervised Learning of Depth and Pose from Monocular Video
Guangming Wang, Jiquan Zhong, Shijie Zhao +3
Depth and ego-motion estimations are essential for the localization and navigation of autonomous robots and autonomous driving. Recent studies make it possible to learn the per-pix…
Efficient 3D Deep LiDAR Odometry
Guangming Wang, Xinrui Wu, Shuyang Jiang +2
An efficient 3D point cloud learning architecture, named EfficientLO-Net, for LiDAR odometry is first proposed in this paper. In this architecture, the projection-aware representat…
Residual 3D Scene Flow Learning with Context-Aware Feature Extraction
Guangming Wang, Yunzhe Hu, Xinrui Wu +1
Scene flow estimation is the task to predict the point-wise or pixel-wise 3D displacement vector between two consecutive frames of point clouds or images, which has important appli…
NccFlow: Unsupervised Learning of Optical Flow With Non-occlusion from Geometry
Guangming Wang, Shuaiqi Ren, Hesheng Wang
Optical flow estimation is a fundamental problem of computer vision and has many applications in the fields of robot learning and autonomous driving. This paper reveals novel geome…
Motion Projection Consistency Based 3D Human Pose Estimation with Virtual Bones from Monocular Videos
Guangming Wang, Honghao Zeng, Ziliang Wang +2
Real-time 3D human pose estimation is crucial for human-computer interaction. It is cheap and practical to estimate 3D human pose only from monocular video. However, recent bone sp…