Fully Sparse Transformer 3-D Detector for LiDAR Point Cloud-Reference-Cited by-同舟云学术

Fully Sparse Transformer 3-D Detector for LiDAR Point Cloud

Published:2023 Issue: Volume:61 Page:1-12
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Zhang Diankun¹^ORCID,Zheng Zhijie¹^ORCID,Niu Haoyu¹,Wang Xueqing¹,Liu Xiaojun¹^ORCID

Affiliation:

1. Aerospace Information Research Institute and the Key Laboratory of Electromagnetic Radiation and Sensing Technology, Chinese Academy of Sciences, Beijing, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10302363.pdf?arnumber=10302363

Reference66 articles.

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

2. Class-balanced grouping and sampling for point cloud 3D object detection;zhu;arXiv 1908 09492,2019

3. Embracing single stride 3D object detector with sparse transformer;fan;arXiv 2112 06375,2021

4. Focal-PETR: Embracing foreground for efficient multi-camera 3D object detection;wang;arXiv 2212 05505,2022

5. From points to parts: 3D object detection from point cloud with part-aware and part-aggregation network;shi;arXiv 1907 03670,2019

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