HPV-RCNN: Hybrid Point–Voxel Two-Stage Network for LiDAR-Based 3-D Object Detection-Reference-Cited by-同舟云学术

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HPV-RCNN: Hybrid Point–Voxel Two-Stage Network for LiDAR-Based 3-D Object Detection

Published:2023-12 Issue:6 Volume:10 Page:3066-3076
ISSN:2329-924X
Container-title:IEEE Transactions on Computational Social Systems
language:
Short-container-title:IEEE Trans. Comput. Soc. Syst.

Author:

Feng Chen¹^ORCID,Xiang Chao¹^ORCID,Xie Xiaopo¹^ORCID,Zhang Yuan¹^ORCID,Yang Mingchuan¹,Li Xuesong²^ORCID

Affiliation:

1. China Telecom Corporation Ltd., Beijing Research Institute, Beijing, China

2. School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China

Funder

National Natural Science Foundation of China

Beijing Municipal Natural Science Foundation

Key Research Project of China Telecom Research Institute

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Human-Computer Interaction,Social Sciences (miscellaneous),Modeling and Simulation

Link

http://xplorestaging.ieee.org/ielx7/6570650/10352175/10177748.pdf?arnumber=10177748

Reference41 articles.

1. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

2. 3DSSD: Point-Based 3D Single Stage Object Detector

3. Deep Hough Voting for 3D Object Detection in Point Clouds

4. Frustum PointNets for 3D Object Detection from RGB-D Data

5. VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection

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