Advanced LiDAR Translation for Huge Domain Gap to Handle Adverse Weather Change-Reference-Cited by-同舟云学术

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Advanced LiDAR Translation for Huge Domain Gap to Handle Adverse Weather Change

Published:2023-06 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring)
language:
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Author:

Lee Jinho¹,Bang Geonkyu¹,Nishimori Toshiaki²,Nakao Kenta³,Kamijo Shunsuke⁴

Affiliation:

1. The University of Tokyo,Emerging Design and Informatics Course, Graduate School of Interdisciplinary Information Studies,Meguro City, Tokyo,Japan,153-0041

2. Mitsubishi Heavy Industries Machinery Systems Ltd.,Hyogo-ku, Kobe,Japan,652-8585

3. Mitsubishi Heavy Industries Ltd.,Hyogo-ku, Kobe,Japan,652-8585

4. The University of Tokyo,The Institute of Industrial Science (IIS),Meguro City, Tokyo,Japan,153-0041

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10199114/10199145/10200824.pdf?arnumber=10200824

Reference16 articles.

1. CNN-Based Lidar Point Cloud De-Noising in Adverse Weather

2. Lidar sensor modeling and data augmentation with gans for autonomous driving;el sallab,2019

3. RePCD-Net: Feature-Aware Recurrent Point Cloud Denoising Network

4. A scalable statistical filter for removing falling snow from lidar point clouds in severe winter weather;kurup,2021

5. Performance modeling a near-infrared tof lidar under fog: A data-driven approach;yang;IEEE Trans Intell Transp Syst,2021

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