Semantic Segmentation for Full-Waveform LiDAR Data Using Local and Hierarchical Global Feature Extraction

Published in ACM SIGSPATIAL 2020, 2020

Recommended citation: Takayuki Shinohara, Haoyi Xiu, and Masashi Matsuoka. 2020. Semantic Segmentation for Full-Waveform LiDAR Data Using Local and Hierarchical Global Feature Extraction. In 28th International Conference on Advances in Geographic Information Systems (SIGSPATIAL 2020), November 3–6, 2020, Seattle, WA, USA. ACM, New York, NY, USA, 11 pages. https://doi.org/10.1145/3397536.3422209 https://dl.acm.org/doi/10.1145/3397536.3422209

This paper is about a novel semantic segmentation method for raw full waveform lidar data, using spatial deep learning method.

Download paper here

Recommended citation: Takayuki Shinohara, Haoyi Xiu, and Masashi Matsuoka. 2020. Semantic Segmentation for Full-Waveform LiDAR Data Using Local and Hierarchical Global Feature Extraction. In 28th International Conference on Advances in Geographic Information Systems (SIGSPATIAL ’20), November 3–6, 2020, Seattle, WA, USA. ACM, New York, NY, USA, 11 pages. https://doi.org/10.1145/3397536.3422209