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Sparse 3D convolutional neural networks

arXiv 1505.02890 ↗First posted 12 May 2015cs.CVcited by 71

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Abstract (arXiv)

We have implemented a convolutional neural network designed for processing sparse three-dimensional input data. The world we live in is three dimensional so there are a large number of potential applications including 3D object recognition and analysis of space-time objects. In the quest for efficiency, we experiment with CNNs on the 2D triangular-lattice and 3D tetrahedral-lattice.

Key facts. Cited by 71 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 May 2015.

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Citing papers per year: 2021: 16; 2022: 15; 2023: 18; 2024: 9; 2025: 10; 2026: 3.

71 papers.

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  1. 2025Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generationcited by 342
  2. 2021An End-to-End Transformer Model for 3D Object Detectioncited by 329
  3. 2021Self-Supervised Pretraining of 3D Features on any Point-Cloudcited by 217
  4. 2023Act3D: 3D Feature Field Transformers for Multi-Task Robotic Manipulationcited by 135
  5. 20223D-SPS: Single-Stage 3D Visual Grounding via Referred Point Progressive Selectioncited by 109
  6. 2021One Thing One Click: A Self-Training Approach for Weakly Supervised 3D Semantic Segmentationcited by 89
  7. 2021Sparse Tensor-based Multiscale Representation for Point Cloud Geometry Compressioncited by 69
  8. 2021Behind the Curtain: Learning Occluded Shapes for 3D Object Detectioncited by 58
  9. 2021Semantics for Robotic Mapping, Perception and Interaction: A Surveycited by 56
  10. 2022Contrastive Boundary Learning for Point Cloud Segmentationcited by 56
  11. 2024SAFDNet: A Simple and Effective Network for Fully Sparse 3D Object Detectioncited by 52
  12. 2022Green Hierarchical Vision Transformer for Masked Image Modelingcited by 50
38 more
  1. 20213D-to-2D Distillation for Indoor Scene Parsingcited by 47
  2. 2021Keypoints-Based Deep Feature Fusion for Cooperative Vehicle Detection of Autonomous Drivingcited by 45
  3. 2023HEDNet: A Hierarchical Encoder-Decoder Network for 3D Object Detection in Point Cloudscited by 45
  4. 2023Nerflets: Local Radiance Fields for Efficient Structure-Aware 3D Scene Representation from 2D Supervisioncited by 44
  5. 2022PointDistiller: Structured Knowledge Distillation Towards Efficient and Compact 3D Detectioncited by 33
  6. 2023Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentationcited by 33
  7. 2022A Unified Query-based Paradigm for Point Cloud Understandingcited by 32
  8. 2022Enable Deep Learning on Mobile Devices: Methods, Systems, and Applicationscited by 32
  9. 2024PO3AD: Predicting Point Offsets toward Better 3D Point Cloud Anomaly Detectioncited by 30
  10. 2021Bootstrap Your Own Correspondencescited by 27
  11. 2021From Voxel to Point: IoU-guided 3D Object Detection for Point Cloud with Voxel-to-Point Decodercited by 23
  12. 2022Sparse Cross-scale Attention Network for Efficient LiDAR Panoptic Segmentationcited by 22
  13. 2022Rethinking IoU-based Optimization for Single-stage 3D Object Detectioncited by 19
  14. 2023TriVol: Point Cloud Rendering via Triple Volumescited by 16
  15. 2021Anchor-free 3D Single Stage Detector with Mask-Guided Attention for Point Cloudcited by 13
  16. 2023Point2Pix: Photo-Realistic Point Cloud Rendering via Neural Radiance Fieldscited by 12
  17. 2021Deep Learning Based 3D Point Cloud Regression for Estimating Forest Biomasscited by 11
  18. 2021SparseConvMIL: Sparse Convolutional Context-Aware Multiple Instance Learning for Whole Slide Image Classificationcited by 10
  19. 2022Data Efficient 3D Learner via Knowledge Transferred from 2D Modelcited by 10
  20. 2023OA-DET3D: Embedding Object Awareness as a General Plug-in for Multi-Camera 3D Object Detectioncited by 7
  21. 2022Towards 3D Scene Understanding by Referring Synthetic Modelscited by 6
  22. 2023Region-Enhanced Feature Learning for Scene Semantic Segmentationcited by 6
  23. 2023Ada3D : Exploiting the Spatial Redundancy with Adaptive Inference for Efficient 3D Object Detectioncited by 6
  24. 2024Improving Distant 3D Object Detection Using 2D Box Supervisioncited by 6
  25. 2022Self-Supervised Correspondence Estimation via Multiview Registrationcited by 5
  26. 2023Content-Adaptive Downsampling in Convolutional Neural Networkscited by 5
  27. 2024Optimized CNNs for Rapid 3D Point Cloud Object Recognitioncited by 5
  28. 2023SPADE: Sparse Pillar-based 3D Object Detection Accelerator for Autonomous Drivingcited by 4
  29. 2023Cross-modal & Cross-domain Learning for Unsupervised LiDAR Semantic Segmentationcited by 4
  30. 2024Panoptic Perception for Autonomous Driving: A Surveycited by 4
  31. 2025LEO-VL: Efficient Scene Representation for Scalable 3D Vision-Language Learningcited by 4
  32. 2022Survey and Systematization of 3D Object Detection Models and Methodscited by 3
  33. 2024Selectively Dilated Convolution for Accuracy-Preserving Sparse Pillar-based Embedded 3D Object Detectioncited by 3
  34. 2021Music source separation conditioned on 3D point cloudscited by 2
  35. 2021A Novel 3D-UNet Deep Learning Framework Based on High-Dimensional Bilateral Grid for Edge Consistent Single Image Depth Estimationcited by 2
  36. 2023Exploiting Sparsity in Automotive Radar Object Detection Networkscited by 2
  37. 2023Sparse and Privacy-enhanced Representation for Human Pose Estimationcited by 2
  38. 2023Revisiting Multi-modal 3D Semantic Segmentation in Real-world Autonomous Drivingcited by 2

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