mlsanityData to 7 Oct 2026

Radar-Camera Fusion for Object Detection and Semantic Segmentation in Autonomous Driving: A Comprehensive Review

arXiv 2304.10410 ↗First posted 20 Apr 2023cs.CV cs.AI cs.ROcited by 57

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Abstract (arXiv)

Driven by deep learning techniques, perception technology in autonomous driving has developed rapidly in recent years, enabling vehicles to accurately detect and interpret surrounding environment for safe and efficient navigation. To achieve accurate and robust perception capabilities, autonomous vehicles are often equipped with multiple sensors, making sensor fusion a crucial part of the perception system. Among these fused sensors, radars and cameras enable a complementary and cost-effective perception of the surrounding environment regardless of lighting and weather conditions. This review aims to provide a comprehensive guideline for radar-camera fusion, particularly concentrating on perception tasks related to object detection and semantic segmentation.Based on the principles of the radar and camera sensors, we delve into the data processing process and representations, followed by an in-depth analysis and summary of radar-camera fusion datasets. In the review of methodologies in radar-camera fusion, we address interrogative questions, including "why to fuse", "what to fuse", "where to fuse", "when to fuse", and "how to fuse", subsequently discussing various challenges and potential research directions within this domain. To ease the retrieval and comparison of datasets and fusion methods, we also provide an interactive website: https://radar-camera-fusion.github.io.

Key facts. Cited by 57 papers in the map (data through 7 Oct 2026). Builds on 190 of its 389 references that are in the map. First posted on arXiv 20 Apr 2023.

Builds on

190 of 389 references.

References · 190

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50 most cited of 190 All 190 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 9; 2024: 11; 2025: 17; 2026: 20.

57 papers.

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  1. 2023LXL: LiDAR Excluded Lean 3D Object Detection with 4D Imaging Radar and Camera Fusioncited by 57
  2. 2024Unleashing HyDRa: Hybrid Fusion, Depth Consistency and Radar for Unified 3D Perceptioncited by 35
  3. 2023WaterScenes: A Multi-Task 4D Radar-Camera Fusion Dataset and Benchmarks for Autonomous Driving on Water Surfacescited by 34
  4. 2024OmniHD-Scenes: A Next-Generation Multimodal Dataset for Autonomous Drivingcited by 27
  5. 2023Exploring Radar Data Representations in Autonomous Driving: A Comprehensive Reviewcited by 22
  6. 2025Doracamom: Joint 3D Detection and Occupancy Prediction with Multi-view 4D Radars and Cameras for Omnidirectional Perceptioncited by 21
  7. 2024DPFT: Dual Perspective Fusion Transformer for Camera-Radar-based Object Detectioncited by 19
  8. 2024Talk2Radar: Bridging Natural Language with 4D mmWave Radar for 3D Referring Expression Comprehensioncited by 17
  9. 2024MSSF: A 4D Radar and Camera Fusion Framework With Multi-Stage Sampling for 3D Object Detection in Autonomous Drivingcited by 14
  10. 2024WaterVG: Waterway Visual Grounding based on Text-Guided Vision and mmWave Radarcited by 13
  11. 2023ASY-VRNet: Waterway Panoptic Driving Perception Model based on Asymmetric Fair Fusion of Vision and 4D mmWave Radarcited by 11
  12. 2023Radars for Autonomous Driving: A Review of Deep Learning Methods and Challengescited by 10
38 more
  1. 2024CR3DT: Camera-RADAR Fusion for 3D Detection and Trackingcited by 9
  2. 2024Radar and Camera Fusion for Object Detection and Tracking: A Comprehensive Surveycited by 9
  3. 2025RICCARDO: Radar Hit Prediction and Convolution for Camera-Radar 3D Object Detectioncited by 9
  4. 2024UniBEVFusion: Unified Radar-Vision BEVFusion for 3D Object Detectioncited by 7
  5. 2025ZFusion: An Effective Fuser of Camera and 4D Radar for 3D Object Perception in Autonomous Drivingcited by 6
  6. 2023Achelous++: Power-Oriented Water-Surface Panoptic Perception Framework on Edge Devices based on Vision-Radar Fusion and Pruning of Heterogeneous Modalitiescited by 4
  7. 2025USVTrack: USV-Based 4D Radar-Camera Tracking Dataset for Autonomous Driving in Inland Waterwayscited by 4
  8. 2025Wavelet-based Multi-View Fusion of 4D Radar Tensor and Camera for Robust 3D Object Detectioncited by 4
  9. 2023Fuzzy-NMS: Improving 3D Object Detection with Fuzzy Classification in NMScited by 3
  10. 2025RASMD: RGB And SWIR Multispectral Driving Dataset for Robust Perception in Adverse Conditionscited by 3
  11. 2025Generative AI for Autonomous Driving: A Reviewcited by 3
  12. 2025CaRaFFusion: Improving 2D Semantic Segmentation with Camera-Radar Point Cloud Fusion and Zero-Shot Image Inpaintingcited by 2
  13. 2025SFGFusion: Surface Fitting Guided 3D Object Detection with 4D Radar and Camera Fusioncited by 2
  14. 2025Dynamic Granularity Matters: Rethinking Vision Transformers Beyond Fixed Patch Splittingcited by 2
  15. 2025Large Model Enabled Embodied Intelligence for 6G Integrated Perception, Communication, and Computation Networkcited by 2
  16. 2023Enhancing Cross-Dataset Performance of Distracted Driving Detection With Score Softmax Classifier And Dynamic Gaussian Smoothing Supervisioncited by 1
  17. 2024A Resource Efficient Fusion Network for Object Detection in Bird's-Eye View using Camera and Raw Radar Datacited by 1
  18. 2025RadarNeXt: Real-Time and Reliable 3D Object Detector Based On 4D mmWave Imaging Radarcited by 1
  19. 2025MaskAttn-UNet: A Mask Attention-Driven Framework for Universal Low-Resolution Image Segmentationcited by 1
  20. 2025RADLER: Radar Object Detection Leveraging Semantic 3D City Models and Self-Supervised Radar-Image Learningcited by 1
  21. 2025To New Beginnings: A Survey of Unified Perception in Autonomous Vehicle Softwarecited by 1
  22. 20264DRC-OCC: Robust Semantic Occupancy Prediction Through Fusion of 4D Radar and Cameracited by 1
  23. 20264D Radar Meets LiDAR and Camera: Cooperative Perception under Adverse Weathercited by 1
  24. 2023Repurposing SAM for User-Defined Semantics Aware Segmentationcited by 0
  25. 2024ARCH2S: Dataset, Benchmark and Challenges for Learning Exterior Architectural Structures from Point Cloudscited by 0
  26. 2025WS-DETR: Robust Water Surface Object Detection through Vision-Radar Fusion with Detection Transformercited by 0
  27. 2025Active Contour Models Driven by Hyperbolic Mean Curvature Flow for Image Segmentationcited by 0
  28. 20264D-CAAL: 4D Radar-Camera Calibration and Auto-Labeling for Autonomous Drivingcited by 0
  29. 2026WaterVideoQA: ASV-Centric Perception and Rule-Compliant Reasoning via Multi-Modal Agentscited by 0
  30. 2026physfusion: A Transformer-based Dual-Stream Radar and Vision Fusion Framework for Open Water Surface Object Detectioncited by 0
  31. 2026calibfusion: Transformer-Based Differentiable Calibration for Radar-Camera Fusion Detection in Water-Surface Environmentscited by 0
  32. 2026MotiMem: Motion-Aware Approximate Memory for Energy-Efficient Neural Perception in Autonomous Vehiclescited by 0
  33. 2026RAVEN: Radar Adaptive Vision Encoders for Efficient Chirp-wise Object Detection and Segmentationcited by 0
  34. 2026DinoRADE: Full Spectral Radar-Camera Fusion with Vision Foundation Model Features for Multi-class Object Detection in Adverse Weathercited by 0
  35. 2026CLLAP: Contrastive Learning-based LiDAR-Augmented Pretraining for Enhanced Radar-Camera Fusioncited by 0
  36. 2026Control Your Queries: Heterogeneous Query Interaction for Camera-Radar Fusioncited by 0
  37. 2026Towards an End-to-End System for 3D Tracking of Physical Objects in Virtual Immersive Environmentscited by 0
  38. 2026Cross-Modal Navigation with Multi-Agent Reinforcement Learningcited by 0

50 most cited of 57 All 57 (JSON)