activity
20202022
most citedTPCN: Temporal Point Cloud Networks for Motion Forecasting

7 citations · 15 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV20222 cited

From One to Many: Dynamic Cross Attention Networks for LiDAR and Camera Fusion

Rui Wan, Shuangjie Xu, Wei Wu +2

LiDAR and cameras are two complementary sensors for 3D perception in autonomous driving. LiDAR point clouds have accurate spatial and geometry information, while RGB images provide…

cs.CV2022

Sparse Cross-scale Attention Network for Efficient LiDAR Panoptic Segmentation

Shuangjie Xu, Rui Wan, Maosheng Ye +2

Two major challenges of 3D LiDAR Panoptic Segmentation (PS) are that point clouds of an object are surface-aggregated and thus hard to model the long-range dependency especially fo…

cs.CV20216 cited

DRINet: A Dual-Representation Iterative Learning Network for Point Cloud Segmentation

Maosheng Ye, Shuangjie Xu, Tongyi Cao +1

We present a novel and flexible architecture for point cloud segmentation with dual-representation iterative learning. In point cloud processing, different representations have the…

cs.CV20217 cited

TPCN: Temporal Point Cloud Networks for Motion Forecasting

Maosheng Ye, Tongyi Cao, Qifeng Chen

We propose the Temporal Point Cloud Networks (TPCN), a novel and flexible framework with joint spatial and temporal learning for trajectory prediction. Unlike existing approaches t…

cs.CV2020

HVNet: Hybrid Voxel Network for LiDAR Based 3D Object Detection

Maosheng Ye, Shuangjie Xu, Tongyi Cao

We present Hybrid Voxel Network (HVNet), a novel one-stage unified network for point cloud based 3D object detection for autonomous driving. Recent studies show that 2D voxelizatio…