ADNet: Non-Local Affinity Distillation Network for Lightweight Depth Completion With Guidance From Missing LiDAR Points-Reference-Cited by-同舟云学术

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ADNet: Non-Local Affinity Distillation Network for Lightweight Depth Completion With Guidance From Missing LiDAR Points

Published:2024-09 Issue:9 Volume:9 Page:7533-7540
ISSN:2377-3766
Container-title:IEEE Robotics and Automation Letters
language:
Short-container-title:IEEE Robot. Autom. Lett.

Author:

Kim Janghyun¹,Noh Jeonghyun¹^ORCID,Jeong Mingyu¹,Lee Wonju²,Park Yeonchool²^ORCID,Park Jinsun³^ORCID

Affiliation:

1. Department of Information Convergence Engineering (Artificial Intelligence Major), Pusan National University, Busan, South Korea

2. Advanced Robotics Laboratory, CTO, LG Electronics, Seoul, South Korea

3. School of Computer Science and Engineering, Pusan National University, Busan, South Korea

Funder

National Research Foundation of Korea

Korea government

Institute of Information & Communications Technology Planning & Evaluation

Artificial Intelligence Convergence Innovation Human Resources Development

LG Electronics

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/7083369/10601335/10598333.pdf?arnumber=10598333

Reference40 articles.

1. Volumetric Occupancy Mapping With Probabilistic Depth Completion for Robotic Navigation

2. DepthNet: Real-Time LiDAR Point Cloud Depth Completion for Autonomous Vehicles

3. In-Depth Review of Augmented Reality: Tracking Technologies, Development Tools, AR Displays, Collaborative AR, and Security Concerns

4. CSPN++: Learning Context and Resource Aware Convolutional Spatial Propagation Networks for Depth Completion

5. Non-local Spatial Propagation Network for Depth Completion

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