139 citations · 358 across the 13 of their papers we have counts for
5 papers · 1 filter
LiDAR-based Panoptic Segmentation via Dynamic Shifting Network
Fangzhou Hong, Hui Zhou, Xinge Zhu +2
With the rapid advances of autonomous driving, it becomes critical to equip its sensing system with more holistic 3D perception. However, existing works focus on parsing either the…
Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentation
Xinge Zhu, Hui Zhou, Tai Wang +5
State-of-the-art methods for large-scale driving-scene LiDAR segmentation often project the point clouds to 2D space and then process them via 2D convolution. Although this corpora…
Cylinder3D: An Effective 3D Framework for Driving-scene LiDAR Semantic Segmentation
Hui Zhou, Xinge Zhu, Xiao Song +4
State-of-the-art methods for large-scale driving-scene LiDAR semantic segmentation often project and process the point clouds in the 2D space. The projection methods includes spher…
AdaStereo: A Simple and Efficient Approach for Adaptive Stereo Matching
Xiao Song, Guorun Yang, Xinge Zhu +3
Recently, records on stereo matching benchmarks are constantly broken by end-to-end disparity networks. However, the domain adaptation ability of these deep models is quite poor. A…
SegVoxelNet: Exploring Semantic Context and Depth-aware Features for 3D Vehicle Detection from Point Cloud
Hongwei Yi, Shaoshuai Shi, Mingyu Ding +6
3D vehicle detection based on point cloud is a challenging task in real-world applications such as autonomous driving. Despite significant progress has been made, we observe two as…