mlsanityData to 7 Oct 2026

3D Object Detection for Autonomous Driving: A Comprehensive Survey

arXiv 2206.09474 ↗First posted 19 Jun 2022cs.CV cs.AI cs.ROcited by 132

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Abstract (arXiv)

Autonomous driving, in recent years, has been receiving increasing attention for its potential to relieve drivers' burdens and improve the safety of driving. In modern autonomous driving pipelines, the perception system is an indispensable component, aiming to accurately estimate the status of surrounding environments and provide reliable observations for prediction and planning. 3D object detection, which intelligently predicts the locations, sizes, and categories of the critical 3D objects near an autonomous vehicle, is an important part of a perception system. This paper reviews the advances in 3D object detection for autonomous driving. First, we introduce the background of 3D object detection and discuss the challenges in this task. Second, we conduct a comprehensive survey of the progress in 3D object detection from the aspects of models and sensory inputs, including LiDAR-based, camera-based, and multi-modal detection approaches. We also provide an in-depth analysis of the potentials and challenges in each category of methods. Additionally, we systematically investigate the applications of 3D object detection in driving systems. Finally, we conduct a performance analysis of the 3D object detection approaches, and we further summarize the research trends over the years and prospect the future directions of this area.

Key facts. Cited by 132 papers in the map (data through 7 Oct 2026). Builds on 306 of its 386 references that are in the map. First posted on arXiv 19 Jun 2022.

Builds on

306 of 386 references.

References · 306

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50 most cited of 306 All 306 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 14; 2024: 45; 2025: 49; 2026: 24.

132 papers.

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  1. 2024A Survey on 3D Gaussian Splattingcited by 221
  2. 2023MapTRv2: An End-to-End Framework for Online Vectorized HD Map Constructioncited by 192
  3. 2023A Language Agent for Autonomous Drivingcited by 161
  4. 2024OccSora: 4D Occupancy Generation Models as World Simulators for Autonomous Drivingcited by 76
  5. 2024A Survey on Autonomous Driving Datasets: Statistics, Annotation Quality, and a Future Outlookcited by 65
  6. 2023FastPillars: A Deployment-friendly Pillar-based 3D Detectorcited by 39
  7. 2024A Survey on Occupancy Perception for Autonomous Driving: The Information Fusion Perspectivecited by 37
  8. 2023GraphAlign: Enhancing Accurate Feature Alignment by Graph matching for Multi-Modal 3D Object Detectioncited by 34
  9. 2025Detect Anything 3D in the Wildcited by 32
  10. 2024LiDAR-PTQ: Post-Training Quantization for Point Cloud 3D Object Detectioncited by 29
  11. 2025CoSDH: Communication-Efficient Collaborative Perception via Supply-Demand Awareness and Intermediate-Late Hybridizationcited by 27
  12. 2023Grid-Centric Traffic Scenario Perception for Autonomous Driving: A Comprehensive Reviewcited by 25
38 more
  1. 2024Forging Vision Foundation Models for Autonomous Driving: Challenges, Methodologies, and Opportunitiescited by 24
  2. 2024Multi-Space Alignments Towards Universal LiDAR Segmentationcited by 24
  3. 2024Find n' Propagate: Open-Vocabulary 3D Object Detection in Urban Environmentscited by 21
  4. 2024RaCFormer: Towards High-Quality 3D Object Detection via Query-based Radar-Camera Fusioncited by 19
  5. 2025Perspective-Invariant 3D Object Detectioncited by 16
  6. 2024Information Entropy Guided Height-aware Histogram for Quantization-friendly Pillar Feature Encodercited by 14
  7. 2024Unlocking Textual and Visual Wisdom: Open-Vocabulary 3D Object Detection Enhanced by Comprehensive Guidance from Text and Imagecited by 14
  8. 2024MSSF: A 4D Radar and Camera Fusion Framework With Multi-Stage Sampling for 3D Object Detection in Autonomous Drivingcited by 14
  9. 2024HGSFusion: Radar-Camera Fusion with Hybrid Generation and Synchronization for 3D Object Detectioncited by 14
  10. 2025Trajectory Prediction for Autonomous Driving: Progress, Limitations, and Future Directionscited by 14
  11. 2025RENO: Real-Time Neural Compression for 3D LiDAR Point Cloudscited by 12
  12. 2025Robust Single-Stage Fully Sparse 3D Object Detection via Detachable Latent Diffusioncited by 11
  13. 2023Mutual Information-calibrated Conformal Feature Fusion for Uncertainty-Aware Multimodal 3D Object Detection at the Edgecited by 9
  14. 2024Harnessing Uncertainty-aware Bounding Boxes for Unsupervised 3D Object Detectioncited by 9
  15. 2024Radar and Camera Fusion for Object Detection and Tracking: A Comprehensive Surveycited by 9
  16. 2025RaGS: Unleashing 3D Gaussian Splatting from 4D Radar and Monocular Cues for 3D Object Detectioncited by 9
  17. 2024SimpleBEV: Improved LiDAR-Camera Fusion Architecture for 3D Object Detectioncited by 8
  18. 2025Collaborative Perception Datasets for Autonomous Driving: A Reviewcited by 8
  19. 2023OA-DET3D: Embedding Object Awareness as a General Plug-in for Multi-Camera 3D Object Detectioncited by 7
  20. 2024MOS: Model Synergy for Test-Time Adaptation on LiDAR-Based 3D Object Detectioncited by 6
  21. 2024Unsupervised 3D Point Cloud Completion via Multi-view Adversarial Learningcited by 6
  22. 2024Robust Multimodal 3D Object Detection via Modality-Agnostic Decoding and Proximity-based Modality Ensemblecited by 5
  23. 20233DifFusionDet: Diffusion Model for 3D Object Detection with Robust LiDAR-Camera Fusioncited by 4
  24. 2024A Survey of Vision Transformers in Autonomous Driving: Current Trends and Future Directionscited by 4
  25. 2024PoIFusion: Multi-Modal 3D Object Detection via Fusion at Points of Interestcited by 4
  26. 2024Semi-Supervised Object Detection: A Survey on Progress from CNN to Transformercited by 4
  27. 2024Deep Learning for 3D Point Cloud Enhancement: A Surveycited by 4
  28. 2024Street Gaussians without 3D Object Trackercited by 4
  29. 2025DDEQs: Distributional Deep Equilibrium Models through Wasserstein Gradient Flowscited by 4
  30. 2025PF3Det: A Prompted Foundation Feature Assisted Visual LiDAR 3D Detectorcited by 4
  31. 2025A Review of 3D Object Detection with Vision-Language Modelscited by 4
  32. 2023SURE-Val: Safe Urban Relevance Extension and Validationcited by 3
  33. 2024Run-time Monitoring of 3D Object Detection in Automated Driving Systems Using Early Layer Neural Activation Patternscited by 3
  34. 2024HV-BEV: Decoupling Horizontal and Vertical Feature Sampling for Multi-View 3D Object Detectioncited by 3
  35. 2025Edge-Based Multimodal Sensor Data Fusion with Vision Language Models (VLMs) for Real-time Autonomous Vehicle Accident Avoidancecited by 3
  36. 2025AutoHood3D: A Multi-Modal Benchmark for Automotive Hood Design and Fluid-Structure Interactioncited by 3
  37. 2025Invisible Triggers, Visible Threats! Road-Style Adversarial Creation Attack for Visual 3D Detection in Autonomous Drivingcited by 3
  38. 2025Enhancing 3D Semantic Scene Completion with a Refinement Modulecited by 3

50 most cited of 132 All 132 (JSON)