Self-Supervised Single-Line LiDAR Depth Completion-Reference-Cited by-同舟云学术

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Self-Supervised Single-Line LiDAR Depth Completion

Published:2023-11 Issue:11 Volume:8 Page:7320-7327
ISSN:2377-3766
Container-title:IEEE Robotics and Automation Letters
language:
Short-container-title:IEEE Robot. Autom. Lett.

Author:

Hu Junjie¹^ORCID,Fan Chenyou²^ORCID,Guo Xiyue³^ORCID,Zhou Liguang⁴^ORCID,Lam Tin Lun¹^ORCID

Affiliation:

1. Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen, China

2. School of Artificial Intelligence, South China Normal University, Guangzhou, China

3. State Key Lab of CAD&CG, Zhejiang University, Hangzhou, China

4. Chinese University of Hong Kong, Shenzhen, China

Funder

National Natural Science Foundation of China

Shenzhen Science and Technology Program

Shenzhen Institute of Artificial Intelligence and Robotics for Society

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Computer Science Applications,Computer Vision and Pattern Recognition,Mechanical Engineering,Human-Computer Interaction,Biomedical Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/7083369/10254630/10258421.pdf?arnumber=10258421

Reference48 articles.

1. Lifelong-monodepth: Lifelong learning for multi-domain monocular metric depth estimation;hu,2023

2. Learning Guided Convolutional Network for Depth Completion

3. Data-free dense depth distillation;hu,2022

4. LE-VINS: A Robust Solid-State-LiDAR-Enhanced Visual-Inertial Navigation System for Low-Speed Robots

5. PENet: Towards Precise and Efficient Image Guided Depth Completion

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