LEST: Large-scale LiDAR Semantic Segmentation with Transformer

Understand

Large-scale LiDAR-based point cloud semantic segmentation is a critical task in autonomous driving perception.

• Almost all of the previous state-of-the-art LiDAR semantic segmentation methods are variants of sparse 3D convolution.
• Although the Transformer architecture is becoming popular in the field of natural language processing and 2D computer vision, its application to large-scale point cloud semantic segmentation is still limited.
• In this paper, we propose a LiDAR sEmantic Segmentation architecture with pure Transformer, LEST.