mlsanityData to 7 Oct 2026

Joint 3D Proposal Generation and Object Detection from View Aggregation

arXiv 1712.02294 ↗First posted 6 Dec 2017cs.CVcited by 325

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Abstract (arXiv)

We present AVOD, an Aggregate View Object Detection network for autonomous driving scenarios. The proposed neural network architecture uses LIDAR point clouds and RGB images to generate features that are shared by two subnetworks: a region proposal network (RPN) and a second stage detector network. The proposed RPN uses a novel architecture capable of performing multimodal feature fusion on high resolution feature maps to generate reliable 3D object proposals for multiple object classes in road scenes. Using these proposals, the second stage detection network performs accurate oriented 3D bounding box regression and category classification to predict the extents, orientation, and classification of objects in 3D space. Our proposed architecture is shown to produce state of the art results on the KITTI 3D object detection benchmark while running in real time with a low memory footprint, making it a suitable candidate for deployment on autonomous vehicles. Code is at: https://github.com/kujason/avod

Key facts. Cited by 325 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Dec 2017.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 94; 2022: 101; 2023: 69; 2024: 27; 2025: 26; 2026: 8.

325 papers.

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  1. 2022TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Drivingcited by 477
  2. 2022TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformerscited by 464
  3. 2021Multi-Modal Fusion Transformer for End-to-End Autonomous Drivingcited by 372
  4. 2021Categorical Depth Distribution Network for Monocular 3D Object Detectioncited by 326
  5. 2022BEVFormer v2: Adapting Modern Image Backbones to Bird's-Eye-View Recognition via Perspective Supervisioncited by 302
  6. 2021Voxel Transformer for 3D Object Detectioncited by 247
  7. 2021PV-RCNN++: Point-Voxel Feature Set Abstraction With Local Vector Representation for 3D Object Detectioncited by 232
  8. 2022DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detectioncited by 224
  9. 2021One Million Scenes for Autonomous Driving: ONCE Datasetcited by 218
  10. 2021Group-Free 3D Object Detection via Transformerscited by 215
  11. 2022Unifying Voxel-based Representation with Transformer for 3D Object Detectioncited by 202
  12. 2022FUTR3D: A Unified Sensor Fusion Framework for 3D Detectioncited by 194
38 more
  1. 2021Multimodal Virtual Point 3D Detectioncited by 166
  2. 2022Omni3D: A Large Benchmark and Model for 3D Object Detection in the Wildcited by 159
  3. 2021ST3D: Self-training for Unsupervised Domain Adaptation on 3D Object Detectioncited by 158
  4. 2021FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimationcited by 144
  5. 2021Offboard 3D Object Detection from Point Cloud Sequencescited by 144
  6. 2022Focal Sparse Convolutional Networks for 3D Object Detectioncited by 142
  7. 20223D Object Detection for Autonomous Driving: A Comprehensive Surveycited by 132
  8. 2022Not All Points Are Equal: Learning Highly Efficient Point-based Detectors for 3D LiDAR Point Cloudscited by 131
  9. 2021LiDAR R-CNN: An Efficient and Universal 3D Object Detectorcited by 129
  10. 2022Vision-Centric BEV Perception: A Surveycited by 126
  11. 2022DeepInteraction: 3D Object Detection via Modality Interactioncited by 125
  12. 2021SAT: 2D Semantics Assisted Training for 3D Visual Groundingcited by 124
  13. 2022Delving into the Devils of Bird's-eye-view Perception: A Review, Evaluation and Recipecited by 122
  14. 2021SE-SSD: Self-Ensembling Single-Stage Object Detector From Point Cloudcited by 119
  15. 2023Benchmarking Robustness of 3D Object Detection to Common Corruptions in Autonomous Drivingcited by 112
  16. 2021Improving 3D Object Detection with Channel-wise Transformercited by 108
  17. 20213D Object Detection for Autonomous Driving: A Surveycited by 106
  18. 2022Voxel Set Transformer: A Set-to-Set Approach to 3D Object Detection from Point Cloudscited by 102
  19. 2021Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attackscited by 101
  20. 2022PillarNet: Real-Time and High-Performance Pillar-based 3D Object Detectioncited by 99
  21. 2021SPG: Unsupervised Domain Adaptation for 3D Object Detection via Semantic Point Generationcited by 93
  22. 2021FusionPainting: Multimodal Fusion with Adaptive Attention for 3D Object Detectioncited by 92
  23. 2023Collaborative Perception in Autonomous Driving: Methods, Datasets and Challengescited by 87
  24. 2021Depth-conditioned Dynamic Message Propagation for Monocular 3D Object Detectioncited by 84
  25. 2022Surface Representation for Point Cloudscited by 84
  26. 2022Sparse Fuse Dense: Towards High Quality 3D Detection with Depth Completioncited by 82
  27. 2023Virtual Sparse Convolution for Multimodal 3D Object Detectioncited by 81
  28. 2023CRN: Camera Radar Net for Accurate, Robust, Efficient 3D Perceptioncited by 81
  29. 2023LoGoNet: Towards Accurate 3D Object Detection with Local-to-Global Cross-Modal Fusioncited by 80
  30. 2021Pyramid R-CNN: Towards Better Performance and Adaptability for 3D Object Detectioncited by 79
  31. 2021SimNet: Learning Reactive Self-driving Simulations from Real-world Observationscited by 77
  32. 2021M3DeTR: Multi-representation, Multi-scale, Mutual-relation 3D Object Detection with Transformerscited by 74
  33. 2022Multi-modal Sensor Fusion for Auto Driving Perception: A Surveycited by 73
  34. 2022LiDAR Snowfall Simulation for Robust 3D Object Detectioncited by 72
  35. 2022AutoAlign: Pixel-Instance Feature Aggregation for Multi-Modal 3D Object Detectioncited by 70
  36. 20223D Object Detection from Images for Autonomous Driving: A Surveycited by 66
  37. 2022CRAFT: Camera-Radar 3D Object Detection with Spatio-Contextual Fusion Transformercited by 66
  38. 2021Multi-Modal 3D Object Detection in Autonomous Driving: a Surveycited by 63

50 most cited of 325 All 325 (JSON)