mlsanityData to 7 Oct 2026

Benchmarking Robustness of 3D Object Detection to Common Corruptions in Autonomous Driving

arXiv 2303.11040 ↗First posted 20 Mar 2023cs.CV cs.AI cs.CRcited by 112

Not on the map. Why?

Abstract (arXiv)

3D object detection is an important task in autonomous driving to perceive the surroundings. Despite the excellent performance, the existing 3D detectors lack the robustness to real-world corruptions caused by adverse weathers, sensor noises, etc., provoking concerns about the safety and reliability of autonomous driving systems. To comprehensively and rigorously benchmark the corruption robustness of 3D detectors, in this paper we design 27 types of common corruptions for both LiDAR and camera inputs considering real-world driving scenarios. By synthesizing these corruptions on public datasets, we establish three corruption robustness benchmarks -- KITTI-C, nuScenes-C, and Waymo-C. Then, we conduct large-scale experiments on 24 diverse 3D object detection models to evaluate their corruption robustness. Based on the evaluation results, we draw several important findings, including: 1) motion-level corruptions are the most threatening ones that lead to significant performance drop of all models; 2) LiDAR-camera fusion models demonstrate better robustness; 3) camera-only models are extremely vulnerable to image corruptions, showing the indispensability of LiDAR point clouds. We release the benchmarks and codes at https://github.com/kkkcx/3D_Corruptions_AD. We hope that our benchmarks and findings can provide insights for future research on developing robust 3D object detection models.

Key facts. Cited by 112 papers in the map (data through 7 Oct 2026). Builds on 59 of its 81 references that are in the map. First posted on arXiv 20 Mar 2023.

Builds on

59 of 81 references.

References · 59

  1. 2020End-to-End Object Detection with Transformerscited by 7,384
  2. 2014Explaining and Harnessing Adversarial Examplescited by 7,287
  3. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,223
  4. 2017mixup: Beyond Empirical Risk Minimizationcited by 5,155
  5. 2013Intriguing properties of neural networkscited by 5,114
  6. 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,485
  7. 2019CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Featurescited by 2,875
  8. 2019Benchmarking Neural Network Robustness to Common Corruptions and Perturbationscited by 2,857
  9. 2019Scalability in Perception for Autonomous Driving: Waymo Open Datasetcited by 2,436
  10. 2020The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalizationcited by 1,842
  11. 2018PointPillars: Fast Encoders for Object Detection from Point Cloudscited by 1,707
  12. 2018ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustnesscited by 1,430
38 more
  1. 2017VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detectioncited by 1,323
  2. 2022BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformerscited by 1,213
  3. 2020Center-based 3D Object Detection and Trackingcited by 1,143
  4. 2018PointRCNN: 3D Object Proposal Generation and Detection from Point Cloudcited by 939
  5. 2019PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detectioncited by 890
  6. 2022BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representationcited by 844
  7. 2016Multi-View 3D Object Detection Network for Autonomous Drivingcited by 721
  8. 2021DETR3D: 3D Object Detection from Multi-view Images via 3D-to-2D Queriescited by 655
  9. 2017Frustum PointNets for 3D Object Detection from RGB-D Datacited by 640
  10. 2019Scaling Out-of-Distribution Detection for Real-World Settingscited by 465
  11. 2022TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformerscited by 464
  12. 2018Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Drivingcited by 455
  13. 2019PointPainting: Sequential Fusion for 3D Object Detectioncited by 449
  14. 2021FCOS3D: Fully Convolutional One-Stage Monocular 3D Object Detectioncited by 444
  15. 20203DSSD: Point-based 3D Single Stage Object Detectorcited by 440
  16. 2019From Points to Parts: 3D Object Detection from Point Cloud with Part-aware and Part-aggregation Networkcited by 366
  17. 2019Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Comingcited by 332
  18. 2017Joint 3D Proposal Generation and Object Detection from View Aggregationcited by 325
  19. 20163D Bounding Box Estimation Using Deep Learning and Geometrycited by 277
  20. 2020Deep Continuous Fusion for Multi-Sensor 3D Object Detectioncited by 263
  21. 2018Generalisation in humans and deep neural networkscited by 237
  22. 2021One Million Scenes for Autonomous Driving: ONCE Datasetcited by 218
  23. 2020SMOKE: Single-Stage Monocular 3D Object Detection via Keypoint Estimationcited by 202
  24. 2022FUTR3D: A Unified Sensor Fusion Framework for 3D Detectioncited by 194
  25. 2021Probabilistic and Geometric Depth: Detecting Objects in Perspectivecited by 190
  26. 2020EPNet: Enhancing Point Features with Image Semantics for 3D Object Detectioncited by 164
  27. 2021ImVoxelNet: Image to Voxels Projection for Monocular and Multi-View General-Purpose 3D Object Detectioncited by 157
  28. 2021SegmentMeIfYouCan: A Benchmark for Anomaly Segmentationcited by 150
  29. 2022Focal Sparse Convolutional Networks for 3D Object Detectioncited by 142
  30. 2022Delving into the Devils of Bird's-eye-view Perception: A Review, Evaluation and Recipecited by 122
  31. 2016Lost and Found: Detecting Small Road Hazards for Self-Driving Vehiclescited by 117
  32. 2022CODA: A Real-World Road Corner Case Dataset for Object Detection in Autonomous Drivingcited by 100
  33. 2021Fog Simulation on Real LiDAR Point Clouds for 3D Object Detection in Adverse Weathercited by 95
  34. 2020Canadian Adverse Driving Conditions Datasetcited by 86
  35. 2022Benchmarking Robustness of 3D Point Cloud Recognition Against Common Corruptionscited by 78
  36. 2020SSN: Shape Signature Networks for Multi-class Object Detection from Point Cloudscited by 74
  37. 2022LiDAR Snowfall Simulation for Robust 3D Object Detectioncited by 72
  38. 2022Benchmarking and Analyzing Point Cloud Classification under Corruptionscited by 70

50 most cited of 59 All 59 (JSON)

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 17; 2024: 33; 2025: 29; 2026: 33.

112 papers.

Sort:

By area:

  1. 2023Robo3D: Towards Robust and Reliable 3D Perception against Corruptionscited by 128
  2. 2025Don't Shake the Wheel: Momentum-Aware Planning in End-to-End Autonomous Drivingcited by 84
  3. 2023Three Pillars improving Vision Foundation Model Distillation for Lidarcited by 43
  4. 2024Visual Adversarial Attack on Vision-Language Models for Autonomous Drivingcited by 35
  5. 2024GraphBEV: Towards Robust BEV Feature Alignment for Multi-Modal 3D Object Detectioncited by 33
  6. 2023Robustness of SAM: Segment Anything Under Corruptions and Beyondcited by 30
  7. 2023BEVHeight++: Toward Robust Visual Centric 3D Object Detectioncited by 29
  8. 2024Is Your HD Map Constructor Reliable under Sensor Corruptions?cited by 28
  9. 2023Machine Vision Therapy: Multimodal Large Language Models Can Enhance Visual Robustness via Denoising In-Context Learningcited by 27
  10. 2024UniMix: Towards Domain Adaptive and Generalizable LiDAR Semantic Segmentation in Adverse Weathercited by 24
  11. 2023Unified Adversarial Patch for Visible-Infrared Cross-modal Attacks in the Physical Worldcited by 21
  12. 2024RoboFusion: Towards Robust Multi-Modal 3D Object Detection via SAMcited by 20
38 more
  1. 2023CoBEV: Elevating Roadside 3D Object Detection with Depth and Height Complementaritycited by 18
  2. 2024V2X-R: Cooperative LiDAR-4D Radar Fusion with Denoising Diffusion for 3D Object Detectioncited by 18
  3. 2025DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Drivingcited by 17
  4. 2025Perspective-Invariant 3D Object Detectioncited by 16
  5. 2023DIFFender: Diffusion-Based Adversarial Defense against Patch Attackscited by 15
  6. 2023Robustness of Segment Anything Model (SAM) for Autonomous Driving in Adverse Weather Conditionscited by 14
  7. 2023Classification robustness to common optical aberrationscited by 13
  8. 2023ReSimAD: Zero-Shot 3D Domain Transfer for Autonomous Driving with Source Reconstruction and Target Simulationcited by 13
  9. 2024ContrastAlign: Toward Robust BEV Feature Alignment via Contrastive Learning for Multi-Modal 3D Object Detectioncited by 13
  10. 2025Resilient Sensor Fusion under Adverse Sensor Failures via Multi-Modal Expert Fusioncited by 13
  11. 2025REOBench: Benchmarking Robustness of Earth Observation Foundation Modelscited by 13
  12. 2024V2X-DGW: Domain Generalization for Multi-agent Perception under Adverse Weather Conditionscited by 12
  13. 2024Visual Robustness Benchmark for Visual Question Answering (VQA)cited by 12
  14. 2025SafeMap: Robust HD Map Construction from Incomplete Observationscited by 12
  15. 2024An Empirical Study of the Generalization Ability of Lidar 3D Object Detectors to Unseen Domainscited by 10
  16. 2024Omniview-Tuning: Boosting Viewpoint Invariance of Vision-Language Pre-training Modelscited by 9
  17. 2024Cocoon: Robust Multi-Modal Perception with Uncertainty-Aware Sensor Fusioncited by 9
  18. 2025Multi-speaker Attention Alignment for Multimodal Social Interactioncited by 8
  19. 2024SegSTRONG-C: Segmenting Surgical Tools Robustly On Non-adversarial Generated Corruptions -- An EndoVis'24 Challengecited by 7
  20. 2024TripleMixer: A 3D Point Cloud Denoising Model for Adverse Weathercited by 7
  21. 2023RobustCLEVR: A Benchmark and Framework for Evaluating Robustness in Object-centric Learningcited by 6
  22. 2023Realistic Rainy Weather Simulation for LiDARs in CARLA Simulatorcited by 6
  23. 2024MOS: Model Synergy for Test-Time Adaptation on LiDAR-Based 3D Object Detectioncited by 6
  24. 2024HGL: Hierarchical Geometry Learning for Test-time Adaptation in 3D Point Cloud Segmentationcited by 6
  25. 2024ReliOcc: Towards Reliable Semantic Occupancy Prediction via Uncertainty Learningcited by 6
  26. 2025Fully Unified Motion Planning for End-to-End Autonomous Drivingcited by 6
  27. 2025Spatial RoboGrasp: Generalized Robotic Grasping Control Policycited by 6
  28. 2025Foundation Models for Autonomous Driving Perception: A Survey Through Core Capabilitiescited by 6
  29. 2025Stability Under Scrutiny: Benchmarking Representation Paradigms for Online HD Mappingcited by 6
  30. 2026GraphWorld: Long-Horizon Planning with World Models for End-to-End Autonomous Drivingcited by 6
  31. 2023A Comprehensive Study on the Robustness of Image Classification and Object Detection in Remote Sensing: Surveying and Benchmarkingcited by 5
  32. 2024DPO: Dual-Perturbation Optimization for Test-time Adaptation in 3D Object Detectioncited by 5
  33. 2024Real-world Adversarial Defense against Patch Attacks based on Diffusion Modelcited by 5
  34. 2025Can MLLMs Read the Room? A Multimodal Benchmark for Assessing Deception in Multi-Party Social Interactionscited by 5
  35. 2023Multi-Modal 3D Object Detection by Box Matchingcited by 4
  36. 2024Improving Robustness of LiDAR-Camera Fusion Model against Weather Corruption from Fusion Strategy Perspectivecited by 4
  37. 2024Benchmarking the Robustness of Panoptic Segmentation for Automated Drivingcited by 3
  38. 2024Team Samsung-RAL: Technical Report for 2024 RoboDrive Challenge-Robust Map Segmentation Trackcited by 3

50 most cited of 112 All 112 (JSON)