4 citations · 12 across the 7 of their papers we have counts for
11 papers · 1 filter
RLSAC: Reinforcement Learning enhanced Sample Consensus for End-to-End Robust Estimation
Chang Nie, Guangming Wang, Zhe Liu +3
Robust estimation is a crucial and still challenging task, which involves estimating model parameters in noisy environments. Although conventional sampling consensus-based algorith…
DELFlow: Dense Efficient Learning of Scene Flow for Large-Scale Point Clouds
Chensheng Peng, Guangming Wang, Xian Wan Lo +5
Point clouds are naturally sparse, while image pixels are dense. The inconsistency limits feature fusion from both modalities for point-wise scene flow estimation. Previous methods…
3D Scene Flow Estimation on Pseudo-LiDAR: Bridging the Gap on Estimating Point Motion
Chaokang Jiang, Guangming Wang, Yanzi Miao +1
3D scene flow characterizes how the points at the current time flow to the next time in the 3D Euclidean space, which possesses the capacity to infer autonomously the non-rigid mot…
FFPA-Net: Efficient Feature Fusion with Projection Awareness for 3D Object Detection
Chaokang Jiang, Guangming Wang, Jinxing Wu +2
Promising complementarity exists between the texture features of color images and the geometric information of LiDAR point clouds. However, there still present many challenges for…
Unsupervised Learning of 3D Scene Flow with 3D Odometry Assistance
Guangming Wang, Zhiheng Feng, Chaokang Jiang +1
Scene flow represents the 3D motion of each point in the scene, which explicitly describes the distance and the direction of each point's movement. Scene flow estimation is used in…
Interactive Multi-scale Fusion of 2D and 3D Features for Multi-object Tracking
Guangming Wang, Chensheng Peng, Jinpeng Zhang +1
Multiple object tracking (MOT) is a significant task in achieving autonomous driving. Traditional works attempt to complete this task, either based on point clouds (PC) collected b…