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PCAN: 3D Attention Map Learning Using Contextual Information for Point Cloud Based Retrieval

arXiv 1904.09793 ↗First posted 22 Apr 2019cs.CV cs.ROcited by 68

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Abstract (arXiv)

Point cloud based retrieval for place recognition is an emerging problem in vision field. The main challenge is how to find an efficient way to encode the local features into a discriminative global descriptor. In this paper, we propose a Point Contextual Attention Network (PCAN), which can predict the significance of each local point feature based on point context. Our network makes it possible to pay more attention to the task-relevent features when aggregating local features. Experiments on various benchmark datasets show that the proposed network can provide outperformance than current state-of-the-art approaches.

Key facts. Cited by 68 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Apr 2019.

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Citing papers per year: 2021: 23; 2022: 18; 2023: 16; 2024: 8; 2025: 3.

68 papers.

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  1. 2021An End-to-End Transformer Model for 3D Object Detectioncited by 329
  2. 2021Walk in the Cloud: Learning Curves for Point Clouds Shape Analysiscited by 172
  3. 2022Contrastive Boundary Learning for Point Cloud Segmentationcited by 56
  4. 2021Learning Semantic Segmentation of Large-Scale Point Clouds with Random Samplingcited by 51
  5. 2022Improving Point Cloud Based Place Recognition with Ranking-based Loss and Large Batch Trainingcited by 44
  6. 2021PVT: Point-Voxel Transformer for Point Cloud Learningcited by 42
  7. 2021MinkLoc++: Lidar and Monocular Image Fusion for Place Recognitioncited by 41
  8. 2023BEVPlace: Learning LiDAR-based Place Recognition using Bird's Eye View Imagescited by 39
  9. 2021SVT-Net: Super Light-Weight Sparse Voxel Transformer for Large Scale Place Recognitioncited by 36
  10. 2021AdaFusion: Visual-LiDAR Fusion with Adaptive Weights for Place Recognitioncited by 36
  11. 2021Deep Learning-Based Autonomous Driving Systems: A Survey of Attacks and Defensescited by 29
  12. 2021TransLoc3D : Point Cloud based Large-scale Place Recognition using Adaptive Receptive Fieldscited by 29
38 more
  1. 2021BVMatch: Lidar-based Place Recognition Using Bird's-eye View Imagescited by 25
  2. 2022InCloud: Incremental Learning for Point Cloud Place Recognitioncited by 22
  3. 2022CASSPR: Cross Attention Single Scan Place Recognitioncited by 22
  4. 2021Efficient 3D Point Cloud Feature Learning for Large-Scale Place Recognitioncited by 21
  5. 2023LCPR: A Multi-Scale Attention-Based LiDAR-Camera Fusion Network for Place Recognitioncited by 17
  6. 2023I2P-Rec: Recognizing Images on Large-scale Point Cloud Maps through Bird's Eye View Projectionscited by 15
  7. 2021SA-Det3D: Self-Attention Based Context-Aware 3D Object Detectioncited by 13
  8. 2022RMS-FlowNet: Efficient and Robust Multi-Scale Scene Flow Estimation for Large-Scale Point Cloudscited by 13
  9. 2021MinkLoc3D-SI: 3D LiDAR place recognition with sparse convolutions, spherical coordinates, and intensitycited by 12
  10. 2022DGECN: A Depth-Guided Edge Convolutional Network for End-to-End 6D Pose Estimationcited by 12
  11. 2022BioSLAM: A Bio-inspired Lifelong Memory System for General Place Recognitioncited by 12
  12. 2021PC2-PU: Patch Correlation and Point Correlation for Effective Point Cloud Upsamplingcited by 11
  13. 2022ARM3D: Attention-based relation module for indoor 3D object detectioncited by 11
  14. 2022General Place Recognition Survey: Towards the Real-world Autonomy Agecited by 11
  15. 2021AttDLNet: Attention-based DL Network for 3D LiDAR Place Recognitioncited by 10
  16. 2022HiTPR: Hierarchical Transformer for Place Recognition in Point Cloudcited by 10
  17. 2022AutoMerge: A Framework for Map Assembling and Smoothing in City-scale Environmentscited by 10
  18. 2023CrossLoc3D: Aerial-Ground Cross-Source 3D Place Recognitioncited by 10
  19. 2022SphereVLAD++: Attention-based and Signal-enhanced Viewpoint Invariant Descriptorcited by 8
  20. 2025CMMLoc: Advancing Text-to-PointCloud Localization with Cauchy-Mixture-Model Based Frameworkcited by 8
  21. 2024VOLoc: Visual Place Recognition by Querying Compressed Lidar Mapcited by 7
  22. 2021Attention Models for Point Clouds in Deep Learning: A Surveycited by 6
  23. 2021PSE-Match: A Viewpoint-free Place Recognition Method with Parallel Semantic Embeddingcited by 6
  24. 2024MinkUNeXt: Point Cloud-based Large-scale Place Recognition using 3D Sparse Convolutionscited by 6
  25. 2025ForestLPR: LiDAR Place Recognition in Forests Attentioning Multiple BEV Density Imagescited by 6
  26. 2021AttWalk: Attentive Cross-Walks for Deep Mesh Analysiscited by 5
  27. 2021Contextualizing Meta-Learning via Learning to Decomposecited by 5
  28. 2021RPR-Net: A Point Cloud-based Rotation-aware Large Scale Place Recognition Networkcited by 5
  29. 2021Unsupervised Online Learning for Robotic Interestingness with Visual Memorycited by 5
  30. 2022Learning to Register Unbalanced Point Pairscited by 5
  31. 2023CurveCloudNet: Processing Point Clouds with 1D Structurecited by 5
  32. 2023Context-Aware Transformer for 3D Point Cloud Automatic Annotationcited by 5
  33. 2023SEM-GAT: Explainable Semantic Pose Estimation using Learned Graph Attentioncited by 5
  34. 2021Large-Scale Topological Radar Localization Using Learned Descriptorscited by 3
  35. 2022Translation Invariant Global Estimation of Heading Angle Using Sinogram of LiDAR Point Cloudcited by 3
  36. 2023SAT: Size-Aware Transformer for 3D Point Cloud Semantic Segmentationcited by 3
  37. 2023Arbitrary point cloud upsampling via Dual Back-Projection Networkcited by 3
  38. 2024VLAD-BuFF: Burst-aware Fast Feature Aggregation for Visual Place Recognitioncited by 3

50 most cited of 68 All 68 (JSON)