SemanticKITTI is a large-scale outdoor-scene dataset for point cloud semantic segmentation. It is derived from the KITTI Vision Odometry Benchmark which it extends with dense point-wise annotations for the complete 360 field-of-view of the employed automotive LiDAR. The dataset consists of 22 sequences. Overall, the dataset provides 23201 point clouds for training and 20351 for testing.
Source: Cylinder3D: An Effective 3D Framework for Driving-scene LiDAR Semantic SegmentationPaper | Code | Results | Date | Stars |
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