mlsanityData to 14 Oct 2026

BEVFusion: A Simple and Robust LiDAR-Camera Fusion Framework

arXiv 2205.13790 ↗First posted 27 May 2022cs.CVcited by 336

Not on the map. Why?

Cited by 39 in End-to-end autonomous driving, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Fusing the camera and LiDAR information has become a de-facto standard for 3D object detection tasks. Current methods rely on point clouds from the LiDAR sensor as queries to leverage the feature from the image space. However, people discovered that this underlying assumption makes the current fusion framework infeasible to produce any prediction when there is a LiDAR malfunction, regardless of minor or major. This fundamentally limits the deployment capability to realistic autonomous driving scenarios. In contrast, we propose a surprisingly simple yet novel fusion framework, dubbed BEVFusion, whose camera stream does not depend on the input of LiDAR data, thus addressing the downside of previous methods. We empirically show that our framework surpasses the state-of-the-art methods under the normal training settings. Under the robustness training settings that simulate various LiDAR malfunctions, our framework significantly surpasses the state-of-the-art methods by 15.7% to 28.9% mAP. To the best of our knowledge, we are the first to handle realistic LiDAR malfunction and can be deployed to realistic scenarios without any post-processing procedure. The code is available at https://github.com/ADLab-AutoDrive/BEVFusion.

Key facts. Cited by 336 papers in the map (data through 14 Oct 2026). Builds on 57 of its 71 references that are in the map. First posted on arXiv 27 May 2022.

Builds on

57 of 71 references.

References · 57

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,248
  3. 2016Feature Pyramid Networks for Object Detectioncited by 5,036
  4. 2017Squeeze-and-Excitation Networkscited by 4,789
  5. 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,523
  6. 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,401
  7. 2019Scalability in Perception for Autonomous Driving: Waymo Open Datasetcited by 2,451
  8. 2018PointPillars: Fast Encoders for Object Detection from Point Cloudscited by 1,715
  9. 2017VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detectioncited by 1,323
  10. 2022BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformerscited by 1,218
  11. 2020Center-based 3D Object Detection and Trackingcited by 1,144
  12. 2020Lift, Splat, Shoot: Encoding Images From Arbitrary Camera Rigs by Implicitly Unprojecting to 3Dcited by 1,044
38 more
  1. 2018PointRCNN: 3D Object Proposal Generation and Detection from Point Cloudcited by 941
  2. 2019PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detectioncited by 891
  3. 2022BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representationcited by 850
  4. 2016Multi-View 3D Object Detection Network for Autonomous Drivingcited by 724
  5. 2021BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-Viewcited by 713
  6. 2021DETR3D: 3D Object Detection from Multi-view Images via 3D-to-2D Queriescited by 658
  7. 2017Frustum PointNets for 3D Object Detection from RGB-D Datacited by 640
  8. 2022TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformerscited by 466
  9. 2019PointPainting: Sequential Fusion for 3D Object Detectioncited by 449
  10. 2021FCOS3D: Fully Convolutional One-Stage Monocular 3D Object Detectioncited by 447
  11. 20203DSSD: Point-based 3D Single Stage Object Detectorcited by 440
  12. 2019Class-balanced Grouping and Sampling for Point Cloud 3D Object Detectioncited by 350
  13. 2022BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object Detectioncited by 341
  14. 2021Categorical Depth Distribution Network for Monocular 3D Object Detectioncited by 327
  15. 2020Deep Continuous Fusion for Multi-Sensor 3D Object Detectioncited by 263
  16. 2021Is Pseudo-Lidar needed for Monocular 3D Object detection?cited by 249
  17. 2022DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detectioncited by 224
  18. 2018Orthographic Feature Transform for Monocular 3D Object Detectioncited by 202
  19. 2022FUTR3D: A Unified Sensor Fusion Framework for 3D Detectioncited by 194
  20. 2021Probabilistic and Geometric Depth: Detecting Objects in Perspectivecited by 191
  21. 2021Objects are Different: Flexible Monocular 3D Object Detectioncited by 185
  22. 20203D-CVF: Generating Joint Camera and LiDAR Features Using Cross-View Spatial Feature Fusion for 3D Object Detectioncited by 176
  23. 2021Multimodal Virtual Point 3D Detectioncited by 166
  24. 2020EPNet: Enhancing Point Features with Image Semantics for 3D Object Detectioncited by 164
  25. 2019MVX-Net: Multimodal VoxelNet for 3D Object Detectioncited by 163
  26. 2020CenterFusion: Center-based Radar and Camera Fusion for 3D Object Detectioncited by 161
  27. 2021Geometry Uncertainty Projection Network for Monocular 3D Object Detectioncited by 156
  28. 2022M2BEV: Multi-Camera Joint 3D Detection and Segmentation with Unified Birds-Eye View Representationcited by 156
  29. 2020CLOCs: Camera-LiDAR Object Candidates Fusion for 3D Object Detectioncited by 147
  30. 2022Focal Sparse Convolutional Networks for 3D Object Detectioncited by 142
  31. 2021RangeDet:In Defense of Range View for LiDAR-based 3D Object Detectioncited by 140
  32. 2020Pillar-based Object Detection for Autonomous Drivingcited by 137
  33. 2021LiDAR R-CNN: An Efficient and Universal 3D Object Detectorcited by 129
  34. 2021RSN: Range Sparse Net for Efficient, Accurate LiDAR 3D Object Detectioncited by 115
  35. 2021FusionPainting: Multimodal Fusion with Adaptive Attention for 3D Object Detectioncited by 92
  36. 2021AutoShape: Real-Time Shape-Aware Monocular 3D Object Detectioncited by 87
  37. 2021Depth-conditioned Dynamic Message Propagation for Monocular 3D Object Detectioncited by 84
  38. 2021CBNet: A Composite Backbone Network Architecture for Object Detectioncited by 77

50 most cited of 57 All 57 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 20; 2023: 76; 2024: 111; 2025: 85; 2026: 44.

336 papers.

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  1. 2022Planning-oriented Autonomous Drivingcited by 1,087
  2. 2023End-to-end Autonomous Driving: Challenges and Frontierscited by 490
  3. 2023Tri-Perspective View for Vision-Based 3D Semantic Occupancy Predictioncited by 409
  4. 2023DrivingGaussian: Composite Gaussian Splatting for Surrounding Dynamic Autonomous Driving Scenescited by 360
  5. 2023SurroundOcc: Multi-Camera 3D Occupancy Prediction for Autonomous Drivingcited by 316
  6. 2025AutoVLA: A Vision-Language-Action Model for End-to-End Autonomous Driving with Adaptive Reasoning and Reinforcement Fine-Tuningcited by 260
  7. 2023DriveMLM: Aligning Multi-Modal Large Language Models with Behavioral Planning States for Autonomous Drivingcited by 233
  8. 2024GenAD: Generative End-to-End Autonomous Drivingcited by 225
  9. 2023VoxelNeXt: Fully Sparse VoxelNet for 3D Object Detection and Trackingcited by 222
  10. 2023Scene as Occupancycited by 209
  11. 2022Sparse4D: Multi-view 3D Object Detection with Sparse Spatial-Temporal Fusioncited by 162
  12. 2022DETRs with Hybrid Matchingcited by 150
38 more
  1. 2023EmbodiedScan: A Holistic Multi-Modal 3D Perception Suite Towards Embodied AIcited by 147
  2. 20223D Object Detection for Autonomous Driving: A Comprehensive Surveycited by 132
  3. 2022DeepInteraction: 3D Object Detection via Modality Interactioncited by 125
  4. 2022Delving into the Devils of Bird's-eye-view Perception: A Review, Evaluation and Recipecited by 122
  5. 2024UniScene: Unified Occupancy-centric Driving Scene Generationcited by 106
  6. 2023FB-BEV: BEV Representation from Forward-Backward View Transformationscited by 98
  7. 2023COTR: Compact Occupancy TRansformer for Vision-based 3D Occupancy Predictioncited by 96
  8. 2024MagicDrive-V2: High-Resolution Long Video Generation for Autonomous Driving with Adaptive Controlcited by 92
  9. 2024GaussianFormer-2: Probabilistic Gaussian Superposition for Efficient 3D Occupancy Predictioncited by 86
  10. 2023SparseFusion: Fusing Multi-Modal Sparse Representations for Multi-Sensor 3D Object Detectioncited by 83
  11. 2023CRN: Camera Radar Net for Accurate, Robust, Efficient 3D Perceptioncited by 82
  12. 2024RCBEVDet: Radar-camera Fusion in Bird's Eye View for 3D Object Detectioncited by 82
  13. 2022BEVPoolv2: A Cutting-edge Implementation of BEVDet Toward Deploymentcited by 79
  14. 2023SSCBench: A Large-Scale 3D Semantic Scene Completion Benchmark for Autonomous Drivingcited by 75
  15. 2023UniTR: A Unified and Efficient Multi-Modal Transformer for Bird's-Eye-View Representationcited by 74
  16. 2023UniPAD: A Universal Pre-training Paradigm for Autonomous Drivingcited by 73
  17. 2023Bird's-Eye-View Scene Graph for Vision-Language Navigationcited by 72
  18. 2023Cross Modal Transformer: Towards Fast and Robust 3D Object Detectioncited by 70
  19. 2023HM-ViT: Hetero-modal Vehicle-to-Vehicle Cooperative perception with vision transformercited by 70
  20. 2023FusionAD: Multi-modality Fusion for Prediction and Planning Tasks of Autonomous Drivingcited by 67
  21. 2022MSMDFusion: Fusing LiDAR and Camera at Multiple Scales with Multi-Depth Seeds for 3D Object Detectioncited by 62
  22. 2023FocalFormer3D : Focusing on Hard Instance for 3D Object Detectioncited by 58
  23. 2024IS-Fusion: Instance-Scene Collaborative Fusion for Multimodal 3D Object Detectioncited by 57
  24. 2023PonderV2: Pave the Way for 3D Foundation Model with A Universal Pre-training Paradigmcited by 56
  25. 2024DrivingForward: Feed-forward 3D Gaussian Splatting for Driving Scene Reconstruction from Flexible Surround-view Inputcited by 53
  26. 2024MGMap: Mask-Guided Learning for Online Vectorized HD Map Constructioncited by 52
  27. 2024Making Large Language Models Better Planners with Reasoning-Decision Alignmentcited by 52
  28. 2022Benchmarking the Robustness of LiDAR-Camera Fusion for 3D Object Detectioncited by 50
  29. 2024Context and Geometry Aware Voxel Transformer for Semantic Scene Completioncited by 50
  30. 2023OccNeRF: Advancing 3D Occupancy Prediction in LiDAR-Free Environmentscited by 41
  31. 2024Benchmarking and Improving Bird's Eye View Perception Robustness in Autonomous Drivingcited by 41
  32. 2022SuperFusion: Multilevel LiDAR-Camera Fusion for Long-Range HD Map Generationcited by 39
  33. 2022X-Align: Cross-Modal Cross-View Alignment for Bird's-Eye-View Segmentationcited by 38
  34. 2023EA-LSS: Edge-aware Lift-splat-shot Framework for 3D BEV Object Detectioncited by 38
  35. 2024A Survey on Occupancy Perception for Autonomous Driving: The Information Fusion Perspectivecited by 37
  36. 2024Unleashing HyDRa: Hybrid Fusion, Depth Consistency and Radar for Unified 3D Perceptioncited by 35
  37. 2024DreamForge: Motion-Aware Autoregressive Video Generation for Multi-View Driving Scenescited by 35
  38. 2023GraphAlign: Enhancing Accurate Feature Alignment by Graph matching for Multi-Modal 3D Object Detectioncited by 34

50 most cited of 336 All 336 (JSON)