17 citations · 51 across the 29 of their papers we have counts for
5 papers · 1 filter
Spherical Frustum Sparse Convolution Network for LiDAR Point Cloud Semantic Segmentation
Yu Zheng, Guangming Wang, Jiuming Liu +2
LiDAR point cloud semantic segmentation enables the robots to obtain fine-grained semantic information of the surrounding environment. Recently, many works project the point cloud…
DifFlow3D: Toward Robust Uncertainty-Aware Scene Flow Estimation with Diffusion Model
Jiuming Liu, Guangming Wang, Weicai Ye +6
Scene flow estimation, which aims to predict per-point 3D displacements of dynamic scenes, is a fundamental task in the computer vision field. However, previous works commonly suff…
SNI-SLAM: Semantic Neural Implicit SLAM
Siting Zhu, Guangming Wang, Hermann Blum +4
We propose SNI-SLAM, a semantic SLAM system utilizing neural implicit representation, that simultaneously performs accurate semantic mapping, high-quality surface reconstruction, a…
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…