mlsanityData to 7 Oct 2026

PointSIFT: A SIFT-like Network Module for 3D Point Cloud Semantic Segmentation

arXiv 1807.00652 ↗First posted 2 Jul 2018cs.CVcited by 58

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Abstract (arXiv)

Recently, 3D understanding research sheds light on extracting features from point cloud directly, which requires effective shape pattern description of point clouds. Inspired by the outstanding 2D shape descriptor SIFT, we design a module called PointSIFT that encodes information of different orientations and is adaptive to scale of shape. Specifically, an orientation-encoding unit is designed to describe eight crucial orientations, and multi-scale representation is achieved by stacking several orientation-encoding units. PointSIFT module can be integrated into various PointNet-based architecture to improve the representation ability. Extensive experiments show our PointSIFT-based framework outperforms state-of-the-art method on standard benchmark datasets. The code and trained model will be published accompanied by this paper.

Key facts. Cited by 58 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Jul 2018.

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Citing papers per year: 2021: 17; 2022: 14; 2023: 9; 2024: 11; 2025: 4; 2026: 3.

58 papers.

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  1. 2021Multi-Modal 3D Object Detection in Autonomous Driving: a Surveycited by 63
  2. 2022STPLS3D: A Large-Scale Synthetic and Real Aerial Photogrammetry 3D Point Cloud Datasetcited by 52
  3. 2023Attention-based Point Cloud Edge Samplingcited by 37
  4. 2021Deep Learning Based 3D Segmentation: A Surveycited by 30
  5. 2022Bidirectional Feature Globalization for Few-shot Semantic Segmentation of 3D Point Cloud Scenescited by 23
  6. 2024General Place Recognition Survey: Towards Real-World Autonomycited by 23
  7. 2024Multimodality Helps Few-shot 3D Point Cloud Semantic Segmentationcited by 20
  8. 2024Rethinking Few-shot 3D Point Cloud Semantic Segmentationcited by 18
  9. 2022Beyond single receptive field: A receptive field fusion-and-stratification network for airborne laser scanning point cloud classificationcited by 16
  10. 2023Sim2real Transfer Learning for Point Cloud Segmentation: An Industrial Application Case on Autonomous Disassemblycited by 16
  11. 2024RAPiD-Seg: Range-Aware Pointwise Distance Distribution Networks for 3D LiDAR Segmentationcited by 15
  12. 2021GA-NET: Global Attention Network for Point Cloud Semantic Segmentationcited by 10
38 more
  1. 2022HiTPR: Hierarchical Transformer for Place Recognition in Point Cloudcited by 10
  2. 2022GeoSegNet: Point Cloud Semantic Segmentation via Geometric Encoder-Decoder Modelingcited by 8
  3. 2021DLA-Net: Learning Dual Local Attention Features for Semantic Segmentation of Large-Scale Building Facade Point Cloudscited by 7
  4. 2021Language-Level Semantics Conditioned 3D Point Cloud Segmentationcited by 7
  5. 2021GSIP: Green Semantic Segmentation of Large-Scale Indoor Point Cloudscited by 7
  6. 2021Investigate Indistinguishable Points in Semantic Segmentation of 3D Point Cloudcited by 6
  7. 2021MKConv: Multidimensional Feature Representation for Point Cloud Analysiscited by 6
  8. 2022Sequential Point Clouds: A Surveycited by 5
  9. 2022Window Normalization: Enhancing Point Cloud Understanding by Unifying Inconsistent Point Densitiescited by 5
  10. 2021Dense Graph Convolutional Neural Networks on 3D Meshes for 3D Object Segmentation and Classificationcited by 4
  11. 2022Understanding the Challenges When 3D Semantic Segmentation Faces Class Imbalanced and OOD Datacited by 4
  12. 2025LiDAR Remote Sensing Meets Weak Supervision: Concepts, Methods, and Perspectivescited by 4
  13. 2021Similarity-Aware Fusion Network for 3D Semantic Segmentationcited by 3
  14. 2021Differentiable Convolution Search for Point Cloud Processingcited by 3
  15. 2022Semantic Segmentation for Point Cloud Scenes via Dilated Graph Feature Aggregation and Pyramid Decoderscited by 3
  16. 2022Learning Spatial and Temporal Variations for 4D Point Cloud Segmentationcited by 3
  17. 2024Advancements in Point Cloud-Based 3D Defect Detection and Classification for Industrial Systems: A Comprehensive Surveycited by 3
  18. 2024On-the-fly Point Feature Representation for Point Clouds Analysiscited by 3
  19. 20213D shape sensing and deep learning-based segmentation of strawberriescited by 2
  20. 2022Completing Partial Point Clouds with Outliers by Collaborative Completion and Segmentationcited by 2
  21. 2022Isomorphic mesh generation from point clouds with multilayer perceptronscited by 1
  22. 2023SynMotor: A Benchmark Suite for Object Attribute Regression and Multi-task Learningcited by 1
  23. 2023GeoSpark: Sparking up Point Cloud Segmentation with Geometry Cluecited by 1
  24. 2023Benchmarking Deep Learning Architectures for Urban Vegetation Point Cloud Semantic Segmentation from MLScited by 1
  25. 2023Deep learning for 3D Object Detection and Tracking in Autonomous Driving: A Brief Surveycited by 1
  26. 2024TraIL-Det: Transformation-Invariant Local Feature Networks for 3D LiDAR Object Detection with Unsupervised Pre-Trainingcited by 1
  27. 2024BelHouse3D: A Benchmark Dataset for Assessing Occlusion Robustness in 3D Point Cloud Semantic Segmentationcited by 1
  28. 2025SAMBLE: Shape-Specific Point Cloud Sampling for an Optimal Trade-Off Between Local Detail and Global Uniformitycited by 1
  29. 2021Learn to Learn Metric Space for Few-Shot Segmentation of 3D Shapescited by 0
  30. 2021Unsupervised Segmentation for Terracotta Warrior with Seed-Region-Growing CNN (SRG-Net)cited by 0
  31. 2021An Evaluation of RGB and LiDAR Fusion for Semantic Segmentationcited by 0
  32. 2021Multi-resolution deep learning pipeline for dense large scale point cloudscited by 0
  33. 2021CT-block: a novel local and global features extractor for point cloudcited by 0
  34. 2022Deep Algebraic Fitting for Multiple Circle Primitives Extraction from Raw Point Cloudscited by 0
  35. 2022HAVANA: Hard negAtiVe sAmples aware self-supervised coNtrastive leArning for Airborne laser scanning point clouds semantic segmentationcited by 0
  36. 2023A Tiny Machine Learning Model for Point Cloud Object Classificationcited by 0
  37. 2023CLIP3Dstyler: Language Guided 3D Arbitrary Neural Style Transfercited by 0
  38. 2023A Review and A Robust Framework of Data-Efficient 3D Scene Parsing with Traditional/Learned 3D Descriptorscited by 0

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