mlsanityData to 14 Oct 2026

Computer Vision for Autonomous Vehicles: Problems, Datasets and State of the Art

arXiv 1704.05519 ↗First posted 18 Apr 2017cs.CV cs.ROcited by 182

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Abstract (arXiv)

Recent years have witnessed enormous progress in AI-related fields such as computer vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it becomes increasingly difficult to stay up-to-date or enter the field as a beginner. While several survey papers on particular sub-problems have appeared, no comprehensive survey on problems, datasets, and methods in computer vision for autonomous vehicles has been published. This book attempts to narrow this gap by providing a survey on the state-of-the-art datasets and techniques. Our survey includes both the historically most relevant literature as well as the current state of the art on several specific topics, including recognition, reconstruction, motion estimation, tracking, scene understanding, and end-to-end learning for autonomous driving. Towards this goal, we analyze the performance of the state of the art on several challenging benchmarking datasets, including KITTI, MOT, and Cityscapes. Besides, we discuss open problems and current research challenges. To ease accessibility and accommodate missing references, we also provide a website that allows navigating topics as well as methods and provides additional information.

Key facts. Cited by 182 papers in the map (data through 14 Oct 2026). First posted on arXiv 18 Apr 2017.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 31; 2022: 34; 2023: 35; 2024: 40; 2025: 24; 2026: 18.

182 papers.

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  1. 2021KITTI-360: A Novel Dataset and Benchmarks for Urban Scene Understanding in 2D and 3Dcited by 575
  2. 2023End-to-end Autonomous Driving: Challenges and Frontierscited by 490
  3. 2024NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarkingcited by 354
  4. 2023A Survey on Multimodal Large Language Models for Autonomous Drivingcited by 290
  5. 2022Panoptic Neural Fields: A Semantic Object-Aware Neural Scene Representationcited by 243
  6. 2021NEAT: Neural Attention Fields for End-to-End Autonomous Drivingcited by 174
  7. 2021A Fine-Grained Analysis on Distribution Shiftcited by 171
  8. 2021E-RAFT: Dense Optical Flow from Event Camerascited by 152
  9. 2022Legged Locomotion in Challenging Terrains using Egocentric Visioncited by 151
  10. 2022KING: Generating Safety-Critical Driving Scenarios for Robust Imitation via Kinematics Gradientscited by 96
  11. 2022SePiCo: Semantic-Guided Pixel Contrast for Domain Adaptive Semantic Segmentationcited by 87
  12. 2022A Deeper Look into Aleatoric and Epistemic Uncertainty Disentanglementcited by 87
38 more
  1. 2021Explanations in Autonomous Driving: A Surveycited by 81
  2. 2021Explainability of deep vision-based autonomous driving systems: Review and challengescited by 80
  3. 2024Local All-Pair Correspondence for Point Trackingcited by 80
  4. 2023ADAPT: Action-aware Driving Caption Transformercited by 78
  5. 2023Milestones in Autonomous Driving and Intelligent Vehicles: Survey of Surveyscited by 75
  6. 2023Semantic Segmentation using Vision Transformers: A surveycited by 73
  7. 2021Multiple Object Tracking with Correlation Learningcited by 67
  8. 2024A Survey on Autonomous Driving Datasets: Statistics, Annotation Quality, and a Future Outlookcited by 66
  9. 2024DMPlug: A Plug-in Method for Solving Inverse Problems with Diffusion Modelscited by 61
  10. 2021Semantics for Robotic Mapping, Perception and Interaction: A Surveycited by 56
  11. 2021Beyond Classification: Directly Training Spiking Neural Networks for Semantic Segmentationcited by 55
  12. 2021Deep Metric Learning for Open World Semantic Segmentationcited by 51
  13. 2021Early Stopping for Deep Image Priorcited by 44
  14. 2023Neural Volumetric Memory for Visual Locomotion Controlcited by 44
  15. 2023Rethinking Confidence Calibration for Failure Predictioncited by 43
  16. 2021A Dynamic Spatial-temporal Attention Network for Early Anticipation of Traffic Accidentscited by 42
  17. 2021MultiSiam: Self-supervised Multi-instance Siamese Representation Learning for Autonomous Drivingcited by 41
  18. 2023All for One, and One for All: UrbanSyn Dataset, the third Musketeer of Synthetic Driving Scenescited by 41
  19. 2022MotionSC: Data Set and Network for Real-Time Semantic Mapping in Dynamic Environmentscited by 40
  20. 2023OpenMix: Exploring Outlier Samples for Misclassification Detectioncited by 38
  21. 2023Convolutional Cross-View Pose Estimationcited by 36
  22. 2023Diversifying the High-level Features for better Adversarial Transferabilitycited by 34
  23. 2025WAFT: Warping-Alone Field Transforms for Optical Flowcited by 34
  24. 2021Pylot: A Modular Platform for Exploring Latency-Accuracy Tradeoffs in Autonomous Vehiclescited by 33
  25. 2022WOODS: Benchmarks for Out-of-Distribution Generalization in Time Seriescited by 30
  26. 2022Block Selection Method for Using Feature Norm in Out-of-distribution Detectioncited by 30
  27. 2024Text2LiDAR: Text-guided LiDAR Point Cloud Generation via Equirectangular Transformercited by 27
  28. 2023Unknown Sniffer for Object Detection: Don't Turn a Blind Eye to Unknown Objectscited by 23
  29. 2022To image, or not to image: Class-specific diffractive cameras with all-optical erasure of undesired objectscited by 21
  30. 2024Is a 3D-Tokenized LLM the Key to Reliable Autonomous Driving?cited by 20
  31. 2021The Hilti SLAM Challenge Datasetcited by 18
  32. 2023360BEV: Panoramic Semantic Mapping for Indoor Bird's-Eye Viewcited by 18
  33. 2023Towards Benchmarking and Assessing Visual Naturalness of Physical World Adversarial Attackscited by 18
  34. 2023Ethical Considerations for Responsible Data Curationcited by 17
  35. 2024Hallucination Detection in Foundation Models for Decision-Making: A Flexible Definition and Review of the State of the Artcited by 17
  36. 2024Towards Generalizable Scene Change Detectioncited by 17
  37. 2022DeepFusion: A Robust and Modular 3D Object Detector for Lidars, Cameras and Radarscited by 16
  38. 2023Delving into Shape-aware Zero-shot Semantic Segmentationcited by 16

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