22 citations · 58 across the 6 of their papers we have counts for
6 papers · 1 filter
RadOcc: Learning Cross-Modality Occupancy Knowledge through Rendering Assisted Distillation
Haiming Zhang, Xu Yan, Dongfeng Bai +5
3D occupancy prediction is an emerging task that aims to estimate the occupancy states and semantics of 3D scenes using multi-view images. However, image-based scene perception enc…
Let Images Give You More:Point Cloud Cross-Modal Training for Shape Analysis
Xu Yan, Heshen Zhan, Chaoda Zheng +4
Although recent point cloud analysis achieves impressive progress, the paradigm of representation learning from a single modality gradually meets its bottleneck. In this work, we t…
2DPASS: 2D Priors Assisted Semantic Segmentation on LiDAR Point Clouds
Xu Yan, Jiantao Gao, Chaoda Zheng +4
As camera and LiDAR sensors capture complementary information used in autonomous driving, great efforts have been made to develop semantic segmentation algorithms through multi-mod…
Box-Aware Feature Enhancement for Single Object Tracking on Point Clouds
Chaoda Zheng, Xu Yan, Jiantao Gao +4
Current 3D single object tracking approaches track the target based on a feature comparison between the target template and the search area. However, due to the common occlusion in…
PointLIE: Locally Invertible Embedding for Point Cloud Sampling and Recovery
Weibing Zhao, Xu Yan, Jiantao Gao +5
Point Cloud Sampling and Recovery (PCSR) is critical for massive real-time point cloud collection and processing since raw data usually requires large storage and computation. In t…
Sparse Single Sweep LiDAR Point Cloud Segmentation via Learning Contextual Shape Priors from Scene Completion
Xu Yan, Jiantao Gao, Jie Li +4
LiDAR point cloud analysis is a core task for 3D computer vision, especially for autonomous driving. However, due to the severe sparsity and noise interference in the single sweep…