mlsanityData to 7 Oct 2026

KPRNet: Improving projection-based LiDAR semantic segmentation

arXiv 2007.12668 ↗First posted 24 Jul 2020cs.CV cs.LGcited by 47

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Abstract (arXiv)

Semantic segmentation is an important component in the perception systems of autonomous vehicles. In this work, we adopt recent advances in both image and point cloud segmentation to achieve a better accuracy in the task of segmenting LiDAR scans. KPRNet improves the convolutional neural network architecture of 2D projection methods and utilizes KPConv to replace the commonly used post-processing techniques with a learnable point-wise component which allows us to obtain more accurate 3D labels. With these improvements our model outperforms the current best method on the SemanticKITTI benchmark, reaching an mIoU of 63.1.

Key facts. Cited by 47 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Jul 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 11; 2022: 11; 2023: 13; 2024: 6; 2025: 4; 2026: 2.

47 papers.

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  1. 2021RPVNet: A Deep and Efficient Range-Point-Voxel Fusion Network for LiDAR Point Cloud Segmentationcited by 173
  2. 2021(AF)2-S3Net: Attentive Feature Fusion with Adaptive Feature Selection for Sparse Semantic Segmentation Networkcited by 164
  3. 2023Rethinking Range View Representation for LiDAR Segmentationcited by 126
  4. 2022Point-to-Voxel Knowledge Distillation for LiDAR Semantic Segmentationcited by 118
  5. 2021Panoptic-PolarNet: Proposal-free LiDAR Point Cloud Panoptic Segmentationcited by 107
  6. 2021EfficientLPS: Efficient LiDAR Panoptic Segmentationcited by 76
  7. 2023RangeViT: Towards Vision Transformers for 3D Semantic Segmentation in Autonomous Drivingcited by 76
  8. 2022Scribble-Supervised LiDAR Semantic Segmentationcited by 69
  9. 2021Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR-based Perceptioncited by 57
  10. 2023UniSeg: A Unified Multi-Modal LiDAR Segmentation Network and the OpenPCSeg Codebasecited by 57
  11. 2022CENet: Toward Concise and Efficient LiDAR Semantic Segmentation for Autonomous Drivingcited by 56
  12. 2023Using a Waffle Iron for Automotive Point Cloud Semantic Segmentationcited by 53
35 more
  1. 2023PointOcc: Cylindrical Tri-Perspective View for Point-based 3D Semantic Occupancy Predictioncited by 51
  2. 2023FRNet: Frustum-Range Networks for Scalable LiDAR Segmentationcited by 50
  3. 2021FIDNet: LiDAR Point Cloud Semantic Segmentation with Fully Interpolation Decodingcited by 46
  4. 2024RangeLDM: Fast Realistic LiDAR Point Cloud Generationcited by 45
  5. 2022LESS: Label-Efficient Semantic Segmentation for LiDAR Point Cloudscited by 41
  6. 2021Lite-HDSeg: LiDAR Semantic Segmentation Using Lite Harmonic Dense Convolutionscited by 37
  7. 2022GFNet: Geometric Flow Network for 3D Point Cloud Semantic Segmentationcited by 36
  8. 2021LIF-Seg: LiDAR and Camera Image Fusion for 3D LiDAR Semantic Segmentationcited by 34
  9. 2023Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentationcited by 33
  10. 2022PointConvFormer: Revenge of the Point-based Convolutioncited by 29
  11. 2021Efficient 3D Deep LiDAR Odometrycited by 25
  12. 2021MVFuseNet: Improving End-to-End Object Detection and Motion Forecasting through Multi-View Fusion of LiDAR Datacited by 18
  13. 2023Instant Domain Augmentation for LiDAR Semantic Segmentationcited by 16
  14. 2022CPGNet: Cascade Point-Grid Fusion Network for Real-Time LiDAR Semantic Segmentationcited by 15
  15. 2022MaskRange: A Mask-classification Model for Range-view based LiDAR Segmentationcited by 15
  16. 2023TFNet: Exploiting Temporal Cues for Fast and Accurate LiDAR Semantic Segmentationcited by 13
  17. 2021S3Net: 3D LiDAR Sparse Semantic Segmentation Networkcited by 9
  18. 2022Uncertainty-aware LiDAR Panoptic Segmentationcited by 6
  19. 2023Retro-FPN: Retrospective Feature Pyramid Network for Point Cloud Semantic Segmentationcited by 6
  20. 2024Deep Learning on 3D Semantic Segmentation: A Detailed Reviewcited by 6
  21. 2023Spherical Frustum Sparse Convolution Network for LiDAR Point Cloud Semantic Segmentationcited by 5
  22. 2024Small, Versatile and Mighty: A Range-View Perception Frameworkcited by 4
  23. 2024Exploiting Local Features and Range Images for Small Data Real-Time Point Cloud Semantic Segmentationcited by 4
  24. 2022Learning Spatial and Temporal Variations for 4D Point Cloud Segmentationcited by 3
  25. 2025FLARES: Fast and Accurate LiDAR Multi-Range Semantic Segmentationcited by 3
  26. 2022A Benchmark for Out of Distribution Detection in Point Cloud 3D Semantic Segmentationcited by 2
  27. 2023Multi-to-Single Knowledge Distillation for Point Cloud Semantic Segmentationcited by 2
  28. 2024Trainable Pointwise Decoder Module for Point Cloud Segmentationcited by 2
  29. 2024PC-BEV: An Efficient Polar-Cartesian BEV Fusion Framework for LiDAR Semantic Segmentationcited by 2
  30. 2023Attention-Guided Lidar Segmentation and Odometry Using Image-to-Point Cloud Saliency Transfercited by 1
  31. 2025Point-Plane Projections for Accurate LiDAR Semantic Segmentation in Small Data Scenarioscited by 1
  32. 2025RangeSAM: On the Potential of Visual Foundation Models for Range-View represented LiDAR segmentationcited by 0
  33. 2025Deep Imbalanced Multi-Target Regression: 3D Point Cloud Voxel Content Estimation in Simulated Forestscited by 0
  34. 2026Contextual Range-View Projection for 3D LiDAR Point Cloudscited by 0
  35. 2026Vanilla ViT for Automotive Point Cloud Semantic Segmentationcited by 0