LIDAR Semantic Segmentation
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Benchmarks
nuScenes
Paris-Lille-3D
SemanticKITTI
S.MID
SemanticSTF
ULS labeled data
Most implemented
Attention Is All You Need
SSD: Single Shot MultiBox Detector
KPConv: Flexible and Deformable Convolution for Point Clouds
RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds
Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution
3D Semantic Segmentation with Submanifold Sparse Convolutional Networks
Papers
No Adaptation Without Observation: Observability-Constrained Test-Time Prompt Tuning for LiDAR Semantic Segmentation
LiDAR semantic segmentation often degrades under real-world deployment due to evolving sensing conditions, while collecting new annotations for retraining is impractical. Test-time adaptation (TTA) updates model paramete…
LIDAR Semantic SegmentationTest-time AdaptationInvascal: Inverse-Vacuity Self-Calibration for Uncertainty-Aware LiDAR Range-View Semantic Segmentation
LiDAR semantic segmentation is a core perception capability for autonomous vehicles and mobile robots. However, safe operation also depends on knowing when predictions are unreliable. Existing approaches typically rely o…
LIDAR Semantic SegmentationAutonomous VehiclesCollaborative Learning for Semi-Supervised LiDAR Semantic Segmentation
Annotating large-scale LiDAR point clouds for 3D semantic segmentation is costly and time-consuming, which motivates the use of semi-supervised learning (SemiSL). Standard LiDAR SemiSL methods typically adopt a two-step …
LIDAR Semantic Segmentation3D Semantic SegmentationPoint CloudsOmniLiDAR: A Unified Diffusion Framework for Multi-Domain 3D LiDAR Generation
LiDAR scene generation is increasingly important for scalable simulation and synthetic data creation, especially under diverse sensing conditions that are costly to capture at scale. Typically, diffusion-based LiDAR gene…
LIDAR Semantic Segmentation3D Object DetectionData AugmentationScene GenerationFeasibility of Indoor Frame-Wise Lidar Semantic Segmentation via Distillation from Visual Foundation Model
Frame-wise semantic segmentation of indoor lidar scans is a fundamental step toward higher-level 3D scene understanding and mapping applications. However, acquiring frame-wise ground truth for training deep learning mode…
LIDAR Semantic SegmentationScene UnderstandingAutonomous DrivingHyperLiDAR: Adaptive Post-Deployment LiDAR Segmentation via Hyperdimensional Computing
LiDAR semantic segmentation plays a pivotal role in 3D scene understanding for edge applications such as autonomous driving. However, significant challenges remain for real-world deployments, particularly for on-device p…
LIDAR Semantic SegmentationScene UnderstandingAutonomous Driving