mlsanityData to 7 Oct 2026

SalsaNet: Fast Road and Vehicle Segmentation in LiDAR Point Clouds for Autonomous Driving

arXiv 1909.08291 ↗First posted 18 Sep 2019cs.CV cs.ROcited by 57

Not on the map. Why?

Abstract (arXiv)

In this paper, we introduce a deep encoder-decoder network, named SalsaNet, for efficient semantic segmentation of 3D LiDAR point clouds. SalsaNet segments the road, i.e. drivable free-space, and vehicles in the scene by employing the Bird-Eye-View (BEV) image projection of the point cloud. To overcome the lack of annotated point cloud data, in particular for the road segments, we introduce an auto-labeling process which transfers automatically generated labels from the camera to LiDAR. We also explore the role of imagelike projection of LiDAR data in semantic segmentation by comparing BEV with spherical-front-view projection and show that SalsaNet is projection-agnostic. We perform quantitative and qualitative evaluations on the KITTI dataset, which demonstrate that the proposed SalsaNet outperforms other state-of-the-art semantic segmentation networks in terms of accuracy and computation time. Our code and data are publicly available at https://gitlab.com/aksoyeren/salsanet.git.

Key facts. Cited by 57 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Sep 2019.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 13; 2022: 9; 2023: 14; 2024: 10; 2025: 7; 2026: 4.

57 papers.

Sort:

By area:

  1. 2021(AF)2-S3Net: Attentive Feature Fusion with Adaptive Feature Selection for Sparse Semantic Segmentation Networkcited by 164
  2. 2023Rethinking Range View Representation for LiDAR Segmentationcited by 126
  3. 2023RangeViT: Towards Vision Transformers for 3D Semantic Segmentation in Autonomous Drivingcited by 76
  4. 2021SQN: Weakly-Supervised Semantic Segmentation of Large-Scale 3D Point Cloudscited by 64
  5. 2021EPMF: Efficient Perception-aware Multi-sensor Fusion for 3D Semantic Segmentationcited by 59
  6. 2023FRNet: Frustum-Range Networks for Scalable LiDAR Segmentationcited by 50
  7. 2022SensatUrban: Learning Semantics from Urban-Scale Photogrammetric Point Cloudscited by 49
  8. 2024Better Call SAL: Towards Learning to Segment Anything in Lidarcited by 47
  9. 2021FIDNet: LiDAR Point Cloud Semantic Segmentation with Fully Interpolation Decodingcited by 46
  10. 2021ConDA: Unsupervised Domain Adaptation for LiDAR Segmentation via Regularized Domain Concatenationcited by 41
  11. 2021Lite-HDSeg: LiDAR Semantic Segmentation Using Lite Harmonic Dense Convolutionscited by 37
  12. 2021Semantic Segmentation-assisted Scene Completion for LiDAR Point Cloudscited by 37
38 more
  1. 2022GFNet: Geometric Flow Network for 3D Point Cloud Semantic Segmentationcited by 36
  2. 2023SSC-RS: Elevate LiDAR Semantic Scene Completion with Representation Separation and BEV Fusioncited by 30
  3. 2021MASS: Multi-Attentional Semantic Segmentation of LiDAR Data for Dense Top-View Understandingcited by 22
  4. 2023Hierarchical Point-based Active Learning for Semi-supervised Point Cloud Semantic Segmentationcited by 21
  5. 2022CPGNet: Cascade Point-Grid Fusion Network for Real-Time LiDAR Semantic Segmentationcited by 15
  6. 2022MaskRange: A Mask-classification Model for Range-view based LiDAR Segmentationcited by 15
  7. 2022COARSE3D: Class-Prototypes for Contrastive Learning in Weakly-Supervised 3D Point Cloud Segmentationcited by 15
  8. 20224DenoiseNet: Adverse Weather Denoising from Adjacent Point Cloudscited by 14
  9. 2024SFPNet: Sparse Focal Point Network for Semantic Segmentation on General LiDAR Point Cloudscited by 13
  10. 2022SemAffiNet: Semantic-Affine Transformation for Point Cloud Segmentationcited by 11
  11. 2021S3Net: 3D LiDAR Sparse Semantic Segmentation Networkcited by 9
  12. 2024Reflectivity Is All You Need!: Advancing LiDAR Semantic Segmentationcited by 9
  13. 2023Lidar Panoptic Segmentation and Tracking without Bells and Whistlescited by 7
  14. 2021Semantics-aware Multi-modal Domain Translation:From LiDAR Point Clouds to Panoramic Color Imagescited by 6
  15. 2024Deep Learning on 3D Semantic Segmentation: A Detailed Reviewcited by 6
  16. 2025Zero-Shot 4D Lidar Panoptic Segmentationcited by 6
  17. 2023On the Calibration of Uncertainty Estimation in LiDAR-based Semantic Segmentationcited by 5
  18. 2023Collect-and-Distribute Transformer for 3D Point Cloud Analysiscited by 4
  19. 2024Off-Road LiDAR Intensity Based Semantic Segmentationcited by 4
  20. 2024Exploiting Local Features and Range Images for Small Data Real-Time Point Cloud Semantic Segmentationcited by 4
  21. 2023PointHR: Exploring High-Resolution Architectures for 3D Point Cloud Segmentationcited by 3
  22. 2024Advancements in Point Cloud-Based 3D Defect Detection and Classification for Industrial Systems: A Comprehensive Surveycited by 3
  23. 2024SeSame: Simple, Easy 3D Object Detection with Point-Wise Semanticscited by 3
  24. 2021AI perspectives in Smart Cities and Communities to enable road vehicle automation and smart traffic controlcited by 2
  25. 2022Point Cloud Semantic Segmentation using Multi Scale Sparse Convolution Neural Networkcited by 2
  26. 2025Point Cloud Based Scene Segmentation: A Surveycited by 2
  27. 2021Detecting Slag Formations with Deep Convolutional Neural Networkscited by 1
  28. 2022On the calibration of underrepresented classes in LiDAR-based semantic segmentationcited by 1
  29. 2023From CAD models to soft point cloud labels: An automatic annotation pipeline for cheaply supervised 3D semantic segmentationcited by 1
  30. 2023Depth- and Semantics-aware Multi-modal Domain Translation: Generating 3D Panoramic Color Images from LiDAR Point Cloudscited by 1
  31. 2025Is clustering enough for LiDAR instance segmentation? A state-of-the-art training-free baselinecited by 1
  32. 2025Point-Plane Projections for Accurate LiDAR Semantic Segmentation in Small Data Scenarioscited by 1
  33. 2021Point Cloud Segmentation Using Sparse Temporal Local Attentioncited by 0
  34. 2023LENet: Lightweight And Efficient LiDAR Semantic Segmentation Using Multi-Scale Convolution Attentioncited by 0
  35. 2023Point2Point : A Framework for Efficient Deep Learning on Hilbert sorted Point Clouds with applications in Spatio-Temporal Occupancy Predictioncited by 0
  36. 2023A Spatiotemporal Correspondence Approach to Unsupervised LiDAR Segmentation with Traffic Applicationscited by 0
  37. 2024Uplifting Range-View-based 3D Semantic Segmentation in Real-Time with Multi-Sensor Fusioncited by 0
  38. 2024TeFF: Tracking-enhanced Forgetting-free Few-shot 3D LiDAR Semantic Segmentationcited by 0

50 most cited of 57 All 57 (JSON)