mlsanityData to 7 Oct 2026

FCOS3D: Fully Convolutional One-Stage Monocular 3D Object Detection

arXiv 2104.10956 ↗First posted 22 Apr 2021cs.CV cs.AI cs.ROcited by 444

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Abstract (arXiv)

Monocular 3D object detection is an important task for autonomous driving considering its advantage of low cost. It is much more challenging than conventional 2D cases due to its inherent ill-posed property, which is mainly reflected in the lack of depth information. Recent progress on 2D detection offers opportunities to better solving this problem. However, it is non-trivial to make a general adapted 2D detector work in this 3D task. In this paper, we study this problem with a practice built on a fully convolutional single-stage detector and propose a general framework FCOS3D. Specifically, we first transform the commonly defined 7-DoF 3D targets to the image domain and decouple them as 2D and 3D attributes. Then the objects are distributed to different feature levels with consideration of their 2D scales and assigned only according to the projected 3D-center for the training procedure. Furthermore, the center-ness is redefined with a 2D Gaussian distribution based on the 3D-center to fit the 3D target formulation. All of these make this framework simple yet effective, getting rid of any 2D detection or 2D-3D correspondence priors. Our solution achieves 1st place out of all the vision-only methods in the nuScenes 3D detection challenge of NeurIPS 2020. Code and models are released at https://github.com/open-mmlab/mmdetection3d.

Key facts. Cited by 444 papers in the map (data through 7 Oct 2026). Builds on 36 of its 44 references that are in the map. First posted on arXiv 22 Apr 2021.

Builds on

36 of 44 references.

References · 36

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
  3. 2016Feature Pyramid Networks for Object Detectioncited by 5,021
  4. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,829
  5. 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,485
  6. 2015SSD: Single Shot MultiBox Detectorcited by 3,125
  7. 2015Fast R-CNNcited by 2,930
  8. 2018PointPillars: Fast Encoders for Object Detection from Point Cloudscited by 1,707
  9. 2019FCOS: Fully Convolutional One-Stage Object Detectioncited by 1,573
  10. 2017Deformable Convolutional Networkscited by 1,481
  11. 2016YOLO9000: Better, Faster, Strongercited by 1,429
  12. 2017VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detectioncited by 1,323
24 more
  1. 2019Objects as Pointscited by 1,172
  2. 2018PointRCNN: 3D Object Proposal Generation and Detection from Point Cloudcited by 939
  3. 2018CornerNet: Detecting Objects as Paired Keypointscited by 763
  4. 2018Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Drivingcited by 455
  5. 2020Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentationcited by 388
  6. 2019Class-balanced Grouping and Sampling for Point Cloud 3D Object Detectioncited by 350
  7. 2019STD: Sparse-to-Dense 3D Object Detector for Point Cloudcited by 282
  8. 20163D Bounding Box Estimation Using Deep Learning and Geometrycited by 277
  9. 2019M3D-RPN: Monocular 3D Region Proposal Network for Object Detectioncited by 251
  10. 2019Disentangling Monocular 3D Object Detectioncited by 215
  11. 2018Orthographic Feature Transform for Monocular 3D Object Detectioncited by 201
  12. 2019Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Drivingcited by 188
  13. 2019Learning Depth-Guided Convolutions for Monocular 3D Object Detectioncited by 169
  14. 2020CenterFusion: Center-based Radar and Camera Fusion for 3D Object Detectioncited by 159
  15. 2020MonoPair: Monocular 3D Object Detection Using Pairwise Spatial Relationshipscited by 153
  16. 2020RTM3D: Real-time Monocular 3D Detection from Object Keypoints for Autonomous Drivingcited by 150
  17. 2018ROI-10D: Monocular Lifting of 2D Detection to 6D Pose and Metric Shapecited by 123
  18. 2020Kinematic 3D Object Detection in Monocular Videocited by 116
  19. 2020End-to-End Pseudo-LiDAR for Image-Based 3D Object Detectioncited by 80
  20. 2020SSN: Shape Signature Networks for Multi-class Object Detection from Point Cloudscited by 74
  21. 2015DenseBox: Unifying Landmark Localization with End to End Object Detectioncited by 58
  22. 2019Monocular 3D Object Detection and Box Fitting Trained End-to-End Using Intersection-over-Union Losscited by 30
  23. 2019Task-Aware Monocular Depth Estimation for 3D Object Detectioncited by 22
  24. 2020Reconfigurable Voxels: A New Representation for LiDAR-Based Point Cloudscited by 16

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 12; 2022: 93; 2023: 135; 2024: 112; 2025: 60; 2026: 32.

444 papers.

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  1. 2022BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformerscited by 1,213
  2. 2022BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representationcited by 844
  3. 2021BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-Viewcited by 711
  4. 2021DETR3D: 3D Object Detection from Multi-view Images via 3D-to-2D Queriescited by 655
  5. 2022BEVDepth: Acquisition of Reliable Depth for Multi-view 3D Object Detectioncited by 568
  6. 2022PETR: Position Embedding Transformation for Multi-View 3D Object Detectioncited by 550
  7. 2023Tri-Perspective View for Vision-Based 3D Semantic Occupancy Predictioncited by 404
  8. 2022PETRv2: A Unified Framework for 3D Perception from Multi-Camera Imagescited by 351
  9. 2022BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object Detectioncited by 340
  10. 2022BEVFusion: A Simple and Robust LiDAR-Camera Fusion Frameworkcited by 334
  11. 2023Occ3D: A Large-Scale 3D Occupancy Prediction Benchmark for Autonomous Drivingcited by 325
  12. 2023Exploring Object-Centric Temporal Modeling for Efficient Multi-View 3D Object Detectioncited by 313
38 more
  1. 2023SurroundOcc: Multi-Camera 3D Occupancy Prediction for Autonomous Drivingcited by 310
  2. 2022BEVFormer v2: Adapting Modern Image Backbones to Bird's-Eye-View Recognition via Perspective Supervisioncited by 302
  3. 2023DriveDreamer: Towards Real-world-driven World Models for Autonomous Drivingcited by 258
  4. 2021Is Pseudo-Lidar needed for Monocular 3D Object detection?cited by 248
  5. 2024EMMA: End-to-End Multimodal Model for Autonomous Drivingcited by 226
  6. 2023Scene as Occupancycited by 208
  7. 2022Unifying Voxel-based Representation with Transformer for 3D Object Detectioncited by 202
  8. 2022FUTR3D: A Unified Sensor Fusion Framework for 3D Detectioncited by 194
  9. 2022BEVerse: Unified Perception and Prediction in Birds-Eye-View for Vision-Centric Autonomous Drivingcited by 191
  10. 2021Probabilistic and Geometric Depth: Detecting Objects in Perspectivecited by 190
  11. 2022Time Will Tell: New Outlooks and A Baseline for Temporal Multi-View 3D Object Detectioncited by 177
  12. 2022Sparse4D: Multi-view 3D Object Detection with Sparse Spatial-Temporal Fusioncited by 161
  13. 2022Omni3D: A Large Benchmark and Model for 3D Object Detection in the Wildcited by 159
  14. 2022M2BEV: Multi-Camera Joint 3D Detection and Segmentation with Unified Birds-Eye View Representationcited by 155
  15. 2024GaussianFormer: Scene as Gaussians for Vision-Based 3D Semantic Occupancy Predictioncited by 155
  16. 2023SparseBEV: High-Performance Sparse 3D Object Detection from Multi-Camera Videoscited by 149
  17. 2022PolarFormer: Multi-camera 3D Object Detection with Polar Transformercited by 147
  18. 2023EmbodiedScan: A Holistic Multi-Modal 3D Perception Suite Towards Embodied AIcited by 146
  19. 20223D Object Detection for Autonomous Driving: A Comprehensive Surveycited by 132
  20. 2022Vision-Centric BEV Perception: A Surveycited by 126
  21. 2023RenderOcc: Vision-Centric 3D Occupancy Prediction with 2D Rendering Supervisioncited by 126
  22. 2022Delving into the Devils of Bird's-eye-view Perception: A Review, Evaluation and Recipecited by 122
  23. 2022ViP3D: End-to-end Visual Trajectory Prediction via 3D Agent Queriescited by 116
  24. 2023PanoOcc: Unified Occupancy Representation for Camera-based 3D Panoptic Segmentationcited by 114
  25. 2023Benchmarking Robustness of 3D Object Detection to Common Corruptions in Autonomous Drivingcited by 112
  26. 2022MonoDTR: Monocular 3D Object Detection with Depth-Aware Transformercited by 108
  27. 2023FB-BEV: BEV Representation from Forward-Backward View Transformationscited by 98
  28. 2021FCAF3D: Fully Convolutional Anchor-Free 3D Object Detectioncited by 97
  29. 2023Visual Point Cloud Forecasting enables Scalable Autonomous Drivingcited by 97
  30. 2023Sparse4D v2: Recurrent Temporal Fusion with Sparse Modelcited by 92
  31. 2022MUTR3D: A Multi-camera Tracking Framework via 3D-to-2D Queriescited by 90
  32. 2022BEVStereo: Enhancing Depth Estimation in Multi-view 3D Object Detection with Dynamic Temporal Stereocited by 89
  33. 2023Symphonize 3D Semantic Scene Completion with Contextual Instance Queriescited by 88
  34. 2022MonoDETR: Depth-guided Transformer for Monocular 3D Object Detectioncited by 85
  35. 2023SparseFusion: Fusing Multi-Modal Sparse Representations for Multi-Sensor 3D Object Detectioncited by 83
  36. 2024GaussianFormer-2: Probabilistic Gaussian Superposition for Efficient 3D Occupancy Predictioncited by 83
  37. 2024RCBEVDet: Radar-camera Fusion in Bird's Eye View for 3D Object Detectioncited by 82
  38. 2023CRN: Camera Radar Net for Accurate, Robust, Efficient 3D Perceptioncited by 81

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