Robust 3D Semantic Segmentation
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Benchmarks
Most implemented
KPConv: Flexible and Deformable Convolution for Point Clouds
4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networks
Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution
SalsaNext: Fast, Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds for Autonomous Driving
Papers
Data-Efficient Point Cloud Semantic Segmentation Pipeline for Unimproved Roads
In this case study, we present a data-efficient point cloud segmentation pipeline and training framework for robust segmentation of unimproved roads and seven other classes. Our method employs a two-stage training framew…
Robust 3D Semantic SegmentationPoint Cloud SegmentationPoint CloudsRobo3D: Towards Robust and Reliable 3D Perception against Corruptions
The robustness of 3D perception systems under natural corruptions from environments and sensors is pivotal for safety-critical applications. Existing large-scale 3D perception datasets often contain data that are meticul…
3D Object Detection3D Semantic SegmentationRobust 3D Object DetectionRobust 3D Semantic SegmentationUsing a Waffle Iron for Automotive Point Cloud Semantic Segmentation
Semantic segmentation of point clouds in autonomous driving datasets requires techniques that can process large numbers of points efficiently. Sparse 3D convolutions have become the de-facto tools to construct deep neura…
3D Semantic SegmentationAutonomous DrivingLIDAR Semantic SegmentationRobust 3D Semantic Segmentation+1PIDS: Joint Point Interaction-Dimension Search for 3D Point Cloud
The interaction and dimension of points are two important axes in designing point operators to serve hierarchical 3D models. Yet, these two axes are heterogeneous and challenging to fully explore. Existing works craft po…
Neural Architecture SearchRobust 3D Semantic SegmentationSemantic SegmentationCENet: Toward Concise and Efficient LiDAR Semantic Segmentation for Autonomous Driving
Accurate and fast scene understanding is one of the challenging task for autonomous driving, which requires to take full advantage of LiDAR point clouds for semantic segmentation. In this paper, we present a \textbf{conc…
3D Semantic SegmentationAutonomous DrivingDescriptiveLIDAR Semantic Segmentation+42DPASS: 2D Priors Assisted Semantic Segmentation on LiDAR Point Clouds
As camera and LiDAR sensors capture complementary information used in autonomous driving, great efforts have been made to develop semantic segmentation algorithms through multi-modality data fusion. However, fusion-based…
3D Semantic SegmentationAutonomous DrivingKnowledge DistillationLIDAR Semantic Segmentation+3