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Datasets/SemanticKITTI

SemanticKITTI

LiDARCC BY-NC-SA 4.0Introduced 2019-01-01

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 Segmentation Image Source: https://github.com/PRBonn/semantic-kitti-api

Benchmarks

10-shot image generation/PQ 10-shot image generation/PQ_dagger 10-shot image generation/PQst 10-shot image generation/PQth 10-shot image generation/RQ 10-shot image generation/RQst 10-shot image generation/RQth 10-shot image generation/SQ 10-shot image generation/SQst 10-shot image generation/SQth 10-shot image generation/mIoU 10-shot image generation/test mIoU 10-shot image generation/val mIoU 10-shot image generation/mIoU-1%10-shot image generation/Speed (FPS)10-shot image generation/Parameters (M)10-shot image generation/mIoU (0.5% Labels)10-shot image generation/mIoU (1% Labels)10-shot image generation/mIoU (2% Labels)10-shot image generation/mIoU (5% Labels)10-shot image generation/mIoU (10% Labels)10-shot image generation/mIoU (20% Labels)10-shot image generation/mIoU (50% Labels)10-shot image generation/mIOU (1% Test set)3D/mIoU 3D Reconstruction/mIoU 3D Scene Reconstruction/mIoU 3D Semantic Scene Completion/mIoU 3D Semantic Segmentation/test mIoU 3D Semantic Segmentation/val mIoU 3D Semantic Segmentation/mIoU-1%3D Semantic Segmentation/Speed (FPS)3D Semantic Segmentation/mIoU 3D Semantic Segmentation/Parameters (M)4D Panoptic Segmentation/LSTQ LIDAR Semantic Segmentation/mIOU LIDAR Semantic Segmentation/val mIoU Lidar Scene Completion/Chamfer Distance Lidar Scene Completion/JSD 3D Lidar Scene Completion/JSD BEV Lidar Scene Completion/Voxel IoU 0.1m Lidar Scene Completion/Voxel IoU 0.2m Lidar Scene Completion/Voxel IoU 0.5m Panoptic Segmentation/PQ Panoptic Segmentation/PQ_dagger Panoptic Segmentation/PQst Panoptic Segmentation/PQth Panoptic Segmentation/RQ Panoptic Segmentation/RQst Panoptic Segmentation/RQth Panoptic Segmentation/SQ Panoptic Segmentation/SQst Panoptic Segmentation/SQth Panoptic Segmentation/mIoU Reconstruction/mIoU Semantic Segmentation/PQ Semantic Segmentation/PQ_dagger Semantic Segmentation/PQst Semantic Segmentation/PQth Semantic Segmentation/RQ Semantic Segmentation/RQst Semantic Segmentation/RQth Semantic Segmentation/SQ Semantic Segmentation/SQst Semantic Segmentation/SQth Semantic Segmentation/mIoU Semantic Segmentation/test mIoU Semantic Segmentation/val mIoU Semantic Segmentation/mIoU-1%Semantic Segmentation/Speed (FPS)Semantic Segmentation/Parameters (M)Semantic Segmentation/mIoU (0.5% Labels)Semantic Segmentation/mIoU (1% Labels)Semantic Segmentation/mIoU (2% Labels)Semantic Segmentation/mIoU (5% Labels)Semantic Segmentation/mIoU (10% Labels)Semantic Segmentation/mIoU (20% Labels)Semantic Segmentation/mIoU (50% Labels)Semantic Segmentation/mIOU (1% Test set)Single-View 3D Reconstruction/mIoU Zero-Shot Learning/HmIoU

Related Benchmarks

SemanticKITTI-C/10-shot image generation/mean Corruption Error (mCE)SemanticKITTI-C/3D Semantic Segmentation/mean Corruption Error (mCE)SemanticKITTI-C/Semantic Segmentation/mean Corruption Error (mCE)

Statistics

Papers: 669
Benchmarks: 81

Links

Tasks

10-shot image generation 3D 3D Reconstruction 3D Scene Reconstruction 3D Semantic Scene Completion 3D Semantic Scene Completion from a single RGB image 3D Semantic Segmentation 4D Panoptic Segmentation Generalized Zero-Shot Learning LIDAR Semantic Segmentation Lidar Scene Completion Panoptic Segmentation Real-Time 3D Semantic Segmentation Reconstruction Semantic Segmentation Semi-Supervised Semantic Segmentation Single-View 3D Reconstruction Weakly supervised Semantic Segmentation Zero-Shot Learning