mlsanityData to 7 Oct 2026

PolarNet: An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentation

arXiv 2003.14032 ↗First posted 31 Mar 2020cs.CVcited by 274

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Abstract (arXiv)

The need for fine-grained perception in autonomous driving systems has resulted in recently increased research on online semantic segmentation of single-scan LiDAR. Despite the emerging datasets and technological advancements, it remains challenging due to three reasons: (1) the need for near-real-time latency with limited hardware; (2) uneven or even long-tailed distribution of LiDAR points across space; and (3) an increasing number of extremely fine-grained semantic classes. In an attempt to jointly tackle all the aforementioned challenges, we propose a new LiDAR-specific, nearest-neighbor-free segmentation algorithm - PolarNet. Instead of using common spherical or bird's-eye-view projection, our polar bird's-eye-view representation balances the points across grid cells in a polar coordinate system, indirectly aligning a segmentation network's attention with the long-tailed distribution of the points along the radial axis. We find that our encoding scheme greatly increases the mIoU in three drastically different segmentation datasets of real urban LiDAR single scans while retaining near real-time throughput.

Key facts. Cited by 274 papers in the map (data through 7 Oct 2026). First posted on arXiv 31 Mar 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 42; 2022: 56; 2023: 69; 2024: 54; 2025: 33; 2026: 20.

274 papers.

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  1. 2021Deep Long-Tailed Learning: A Surveycited by 416
  2. 2023Tri-Perspective View for Vision-Based 3D Semantic Occupancy Predictioncited by 404
  3. 2023OccFormer: Dual-path Transformer for Vision-based 3D Semantic Occupancy Predictioncited by 287
  4. 2021RPVNet: A Deep and Efficient Range-Point-Voxel Fusion Network for LiDAR Point Cloud Segmentationcited by 173
  5. 2021Panoptic nuScenes: A Large-Scale Benchmark for LiDAR Panoptic Segmentation and Trackingcited by 165
  6. 2021(AF)2-S3Net: Attentive Feature Fusion with Adaptive Feature Selection for Sparse Semantic Segmentation Networkcited by 164
  7. 20222DPASS: 2D Priors Assisted Semantic Segmentation on LiDAR Point Cloudscited by 157
  8. 2022PolarFormer: Multi-camera 3D Object Detection with Polar Transformercited by 147
  9. 2021RangeDet:In Defense of Range View for LiDAR-based 3D Object Detectioncited by 140
  10. 2021LiDAR R-CNN: An Efficient and Universal 3D Object Detectorcited by 129
  11. 2023Robo3D: Towards Robust and Reliable 3D Perception against Corruptionscited by 128
  12. 2023Rethinking Range View Representation for LiDAR Segmentationcited by 126
38 more
  1. 2023Spherical Transformer for LiDAR-based 3D Recognitioncited by 124
  2. 2023Segment Any Point Cloud Sequences by Distilling Vision Foundation Modelscited by 123
  3. 2022Delving into the Devils of Bird's-eye-view Perception: A Review, Evaluation and Recipecited by 122
  4. 2021NeSF: Neural Semantic Fields for Generalizable Semantic Segmentation of 3D Scenescited by 119
  5. 2022Point-to-Voxel Knowledge Distillation for LiDAR Semantic Segmentationcited by 118
  6. 2023PanoOcc: Unified Occupancy Representation for Camera-based 3D Panoptic Segmentationcited by 114
  7. 2021Panoptic-PolarNet: Proposal-free LiDAR Point Cloud Panoptic Segmentationcited by 107
  8. 2022CenterFormer: Center-based Transformer for 3D Object Detectioncited by 99
  9. 2021FusionPainting: Multimodal Fusion with Adaptive Attention for 3D Object Detectioncited by 92
  10. 2022LaserMix for Semi-Supervised LiDAR Semantic Segmentationcited by 92
  11. 2021EfficientLPS: Efficient LiDAR Panoptic Segmentationcited by 76
  12. 2023RangeViT: Towards Vision Transformers for 3D Semantic Segmentation in Autonomous Drivingcited by 76
  13. 2022LidarMultiNet: Towards a Unified Multi-Task Network for LiDAR Perceptioncited by 74
  14. 2021Semantic Segmentation for Real Point Cloud Scenes via Bilateral Augmentation and Adaptive Fusioncited by 71
  15. 2023MSeg3D: Multi-modal 3D Semantic Segmentation for Autonomous Drivingcited by 68
  16. 2022SafeBench: A Benchmarking Platform for Safety Evaluation of Autonomous Vehiclescited by 65
  17. 20214D Panoptic LiDAR Segmentationcited by 64
  18. 2021SQN: Weakly-Supervised Semantic Segmentation of Large-Scale 3D Point Cloudscited by 64
  19. 2021Learning 3D Semantic Segmentation with only 2D Image Supervisioncited by 60
  20. 2021EPMF: Efficient Perception-aware Multi-sensor Fusion for 3D Semantic Segmentationcited by 59
  21. 2022Panoptic-PHNet: Towards Real-Time and High-Precision LiDAR Panoptic Segmentation via Clustering Pseudo Heatmapcited by 59
  22. 2021Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR-based Perceptioncited by 57
  23. 2023UniSeg: A Unified Multi-Modal LiDAR Segmentation Network and the OpenPCSeg Codebasecited by 57
  24. 2022CoSMix: Compositional Semantic Mix for Domain Adaptation in 3D LiDAR Segmentationcited by 54
  25. 2022Polar Parametrization for Vision-based Surround-View 3D Detectioncited by 53
  26. 2023Using a Waffle Iron for Automotive Point Cloud Semantic Segmentationcited by 53
  27. 2024Multi-Modal Data-Efficient 3D Scene Understanding for Autonomous Drivingcited by 53
  28. 2022STPLS3D: A Large-Scale Synthetic and Real Aerial Photogrammetry 3D Point Cloud Datasetcited by 52
  29. 2021Learning Semantic Segmentation of Large-Scale Point Clouds with Random Samplingcited by 51
  30. 2023PointOcc: Cylindrical Tri-Perspective View for Point-based 3D Semantic Occupancy Predictioncited by 51
  31. 2023FRNet: Frustum-Range Networks for Scalable LiDAR Segmentationcited by 50
  32. 2022SensatUrban: Learning Semantics from Urban-Scale Photogrammetric Point Cloudscited by 49
  33. 2021FIDNet: LiDAR Point Cloud Semantic Segmentation with Fully Interpolation Decodingcited by 46
  34. 20233D Semantic Segmentation in the Wild: Learning Generalized Models for Adverse-Condition Point Cloudscited by 46
  35. 2021ConDA: Unsupervised Domain Adaptation for LiDAR Segmentation via Regularized Domain Concatenationcited by 41
  36. 2022LESS: Label-Efficient Semantic Segmentation for LiDAR Point Cloudscited by 41
  37. 2021Cross-modal Learning for Domain Adaptation in 3D Semantic Segmentationcited by 40
  38. 2022Density-preserving Deep Point Cloud Compressioncited by 39

50 most cited of 274 All 274 (JSON)