mlsanityData to 14 Oct 2026

LatticeNet: Fast Point Cloud Segmentation Using Permutohedral Lattices

arXiv 1912.05905 ↗First posted 12 Dec 2019cs.CV cs.LG eess.IVcited by 38

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Abstract (arXiv)

Deep convolutional neural networks (CNNs) have shown outstanding performance in the task of semantically segmenting images. However, applying the same methods on 3D data still poses challenges due to the heavy memory requirements and the lack of structured data. Here, we propose LatticeNet, a novel approach for 3D semantic segmentation, which takes as input raw point clouds. A PointNet describes the local geometry which we embed into a sparse permutohedral lattice. The lattice allows for fast convolutions while keeping a low memory footprint. Further, we introduce DeformSlice, a novel learned data-dependent interpolation for projecting lattice features back onto the point cloud. We present results of 3D segmentation on various datasets where our method achieves state-of-the-art performance.

Key facts. Cited by 38 papers in the map (data through 14 Oct 2026). First posted on arXiv 12 Dec 2019.

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Citing papers per year: 2021: 14; 2022: 9; 2023: 8; 2024: 5; 2025: 1; 2026: 1.

38 papers.

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  1. 2021(AF)2-S3Net: Attentive Feature Fusion with Adaptive Feature Selection for Sparse Semantic Segmentation Networkcited by 164
  2. 20222DPASS: 2D Priors Assisted Semantic Segmentation on LiDAR Point Cloudscited by 158
  3. 2021Fast Point Transformercited by 104
  4. 2021SQN: Weakly-Supervised Semantic Segmentation of Large-Scale 3D Point Cloudscited by 64
  5. 2022Contrastive Boundary Learning for Point Cloud Segmentationcited by 56
  6. 2023Using a Waffle Iron for Automotive Point Cloud Semantic Segmentationcited by 53
  7. 2021Learning Semantic Segmentation of Large-Scale Point Clouds with Random Samplingcited by 51
  8. 2022SensatUrban: Learning Semantics from Urban-Scale Photogrammetric Point Cloudscited by 50
  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. 2021Deep Learning Based 3D Segmentation: A Surveycited by 30
26 more
  1. 2021LiDAR-based Recurrent 3D Semantic Segmentation with Temporal Memory Alignmentcited by 26
  2. 2021DRINet++: Efficient Voxel-as-point Point Cloud Segmentationcited by 23
  3. 2022Meta-RangeSeg: LiDAR Sequence Semantic Segmentation Using Multiple Feature Aggregationcited by 23
  4. 2022Scalable SoftGroup for 3D Instance Segmentation on Point Cloudscited by 15
  5. 2022COARSE3D: Class-Prototypes for Contrastive Learning in Weakly-Supervised 3D Point Cloud Segmentationcited by 15
  6. 2024LSK3DNet: Towards Effective and Efficient 3D Perception with Large Sparse Kernelscited by 15
  7. 2024TASeg: Temporal Aggregation Network for LiDAR Semantic Segmentationcited by 13
  8. 2021LatticeNet: Fast Spatio-Temporal Point Cloud Segmentation Using Permutohedral Latticescited by 11
  9. 2021S3Net: 3D LiDAR Sparse Semantic Segmentation Networkcited by 9
  10. 2021Real-time Multi-Adaptive-Resolution-Surfel 6D LiDAR Odometry using Continuous-time Trajectory Optimizationcited by 9
  11. 2022Abstract Flow for Temporal Semantic Segmentation on the Permutohedral Latticecited by 9
  12. 2023Radar Instance Transformer: Reliable Moving Instance Segmentation in Sparse Radar Point Cloudscited by 9
  13. 2023A Review of Panoptic Segmentation for Mobile Mapping Point Cloudscited by 8
  14. 2025Unsupervised deep learning for semantic segmentation of multispectral LiDAR forest point cloudscited by 7
  15. 2021Efficient Urban-scale Point Clouds Segmentation with BEV Projectioncited by 6
  16. 2022Sequential Point Clouds: A Surveycited by 6
  17. 2024Deep Learning on 3D Semantic Segmentation: A Detailed Reviewcited by 6
  18. 2023Knowledge Distillation from 3D to Bird's-Eye-View for LiDAR Semantic Segmentationcited by 4
  19. 2024ESCAPE: Equivariant Shape Completion via Anchor Point Encodingcited by 4
  20. 2023Multi-to-Single Knowledge Distillation for Point Cloud Semantic Segmentationcited by 2
  21. 2024PC-BEV: An Efficient Polar-Cartesian BEV Fusion Framework for LiDAR Semantic Segmentationcited by 2
  22. 2026Resolving Primitive-Sharing Ambiguity in Long-Tailed TLS-Based Industrial MEP Point Cloud Segmentation via Spatial Context Constraintscited by 1
  23. 2022A Near Sensor Edge Computing System for Point Cloud Semantic Segmentationcited by 0
  24. 2023LENet: Lightweight And Efficient LiDAR Semantic Segmentation Using Multi-Scale Convolution Attentioncited by 0
  25. 2023Semantic Segmentation of Urban Textured Meshes Through Point Samplingcited by 0
  26. 2023CLIP3Dstyler: Language Guided 3D Arbitrary Neural Style Transfercited by 0