mlsanityData to 7 Oct 2026

TORNADO-Net: mulTiview tOtal vaRiatioN semAntic segmentation with Diamond inceptiOn module

arXiv 2008.10544 ↗First posted 24 Aug 2020cs.CVcited by 36

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Abstract (arXiv)

Semantic segmentation of point clouds is a key component of scene understanding for robotics and autonomous driving. In this paper, we introduce TORNADO-Net - a neural network for 3D LiDAR point cloud semantic segmentation. We incorporate a multi-view (bird-eye and range) projection feature extraction with an encoder-decoder ResNet architecture with a novel diamond context block. Current projection-based methods do not take into account that neighboring points usually belong to the same class. To better utilize this local neighbourhood information and reduce noisy predictions, we introduce a combination of Total Variation, Lovasz-Softmax, and Weighted Cross-Entropy losses. We also take advantage of the fact that the LiDAR data encompasses 360 degrees field of view and uses circular padding. We demonstrate state-of-the-art results on the SemanticKITTI dataset and also provide thorough quantitative evaluations and ablation results.

Key facts. Cited by 36 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Aug 2020.

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Citing papers per year: 2021: 9; 2022: 11; 2023: 9; 2024: 3; 2025: 2; 2026: 2.

36 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. 2022Delving into the Devils of Bird's-eye-view Perception: A Review, Evaluation and Recipecited by 122
  5. 2022Point-to-Voxel Knowledge Distillation for LiDAR Semantic Segmentationcited by 118
  6. 2021Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR-based Perceptioncited by 57
  7. 2023UniSeg: A Unified Multi-Modal LiDAR Segmentation Network and the OpenPCSeg Codebasecited by 57
  8. 2023Using a Waffle Iron for Automotive Point Cloud Semantic Segmentationcited by 53
  9. 2023FRNet: Frustum-Range Networks for Scalable LiDAR Segmentationcited by 50
  10. 2021FIDNet: LiDAR Point Cloud Semantic Segmentation with Fully Interpolation Decodingcited by 46
  11. 2022LESS: Label-Efficient Semantic Segmentation for LiDAR Point Cloudscited by 41
  12. 2021GP-S3Net: Graph-based Panoptic Sparse Semantic Segmentation Networkcited by 37
24 more
  1. 2022GFNet: Geometric Flow Network for 3D Point Cloud Semantic Segmentationcited by 36
  2. 2021LIF-Seg: LiDAR and Camera Image Fusion for 3D LiDAR Semantic Segmentationcited by 34
  3. 2022Frame Mining: a Free Lunch for Learning Robotic Manipulation from 3D Point Cloudscited by 31
  4. 2022Meta-RangeSeg: LiDAR Sequence Semantic Segmentation Using Multiple Feature Aggregationcited by 23
  5. 2021CPSeg: Cluster-free Panoptic Segmentation of 3D LiDAR Point Cloudscited by 14
  6. 2023MemorySeg: Online LiDAR Semantic Segmentation with a Latent Memorycited by 13
  7. 2021SMAC-Seg: LiDAR Panoptic Segmentation via Sparse Multi-directional Attention Clusteringcited by 11
  8. 2024Deep Learning on 3D Semantic Segmentation: A Detailed Reviewcited by 6
  9. 2021How to Build a Curb Dataset with LiDAR Data for Autonomous Drivingcited by 4
  10. 2022COLA: COarse LAbel pre-training for 3D semantic segmentation of sparse LiDAR datasetscited by 4
  11. 2022Teachers in concordance for pseudo-labeling of 3D sequential datacited by 3
  12. 2025FLARES: Fast and Accurate LiDAR Multi-Range Semantic Segmentationcited by 3
  13. 2022Point Cloud Semantic Segmentation using Multi Scale Sparse Convolution Neural Networkcited by 2
  14. 2023Multi-to-Single Knowledge Distillation for Point Cloud Semantic Segmentationcited by 2
  15. 2023PANet: LiDAR Panoptic Segmentation with Sparse Instance Proposal and Aggregationcited by 2
  16. 2023Attention-Guided Lidar Segmentation and Odometry Using Image-to-Point Cloud Saliency Transfercited by 1
  17. 2023Cross-modal and Cross-domain Knowledge Transfer for Label-free 3D Segmentationcited by 1
  18. 2025Is clustering enough for LiDAR instance segmentation? A state-of-the-art training-free baselinecited by 1
  19. 2022Domain Adaptation in LiDAR Semantic Segmentation via Alternating Skip Connections and Hybrid Learningcited by 0
  20. 2022A Near Sensor Edge Computing System for Point Cloud Semantic Segmentationcited by 0
  21. 2024ELiTe: Efficient Image-to-LiDAR Knowledge Transfer for Semantic Segmentationcited by 0
  22. 2024Uplifting Range-View-based 3D Semantic Segmentation in Real-Time with Multi-Sensor Fusioncited by 0
  23. 2026From Spherical to Gaussian: A Comparative Analysis of Point Cloud Cropping Strategies in Large-Scale 3D Environmentscited by 0
  24. 2026Vanilla ViT for Automotive Point Cloud Semantic Segmentationcited by 0