mlsanityData to 7 Oct 2026

Robustness of Object Detectors in Degrading Weather Conditions

arXiv 2106.08795 ↗First posted 16 Jun 2021cs.CVcited by 28

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Abstract (arXiv)

State-of-the-art object detection systems for autonomous driving achieve promising results in clear weather conditions. However, such autonomous safety critical systems also need to work in degrading weather conditions, such as rain, fog and snow. Unfortunately, most approaches evaluate only on the KITTI dataset, which consists only of clear weather scenes. In this paper we address this issue and perform one of the most detailed evaluation on single and dual modality architectures on data captured in real weather conditions. We analyse the performance degradation of these architectures in degrading weather conditions. We demonstrate that an object detection architecture performing good in clear weather might not be able to handle degrading weather conditions. We also perform ablation studies on the dual modality architectures and show their limitations.

Key facts. Cited by 28 papers in the map (data through 7 Oct 2026). Builds on 37 of its 53 references that are in the map. First posted on arXiv 16 Jun 2021.

Builds on

37 of 53 references.

References · 37

  1. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
  2. 2020End-to-End Object Detection with Transformerscited by 7,384
  3. 2016Feature Pyramid Networks for Object Detectioncited by 5,021
  4. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,829
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  11. 2018PointPillars: Fast Encoders for Object Detection from Point Cloudscited by 1,707
  12. 2016YOLO9000: Better, Faster, Strongercited by 1,429
25 more
  1. 2017VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detectioncited by 1,323
  2. 2017Cascade R-CNN: Delving into High Quality Object Detectioncited by 1,275
  3. 2019EfficientDet: Scalable and Efficient Object Detectioncited by 1,018
  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. 2018CornerNet: Detecting Objects as Paired Keypointscited by 763
  7. 2016Multi-View 3D Object Detection Network for Autonomous Drivingcited by 721
  8. 2019Deep Hough Voting for 3D Object Detection in Point Cloudscited by 648
  9. 2017Frustum PointNets for 3D Object Detection from RGB-D Datacited by 640
  10. 20203DSSD: Point-based 3D Single Stage Object Detectorcited by 440
  11. 2019Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Comingcited by 332
  12. 2017Joint 3D Proposal Generation and Object Detection from View Aggregationcited by 325
  13. 2020Deep Continuous Fusion for Multi-Sensor 3D Object Detectioncited by 263
  14. 2020Multi-Task Multi-Sensor Fusion for 3D Object Detectioncited by 203
  15. 2018Orthographic Feature Transform for Monocular 3D Object Detectioncited by 201
  16. 2019Stereo R-CNN based 3D Object Detection for Autonomous Drivingcited by 163
  17. 2019Fast Point R-CNNcited by 119
  18. 2019Monocular 3D Object Detection Leveraging Accurate Proposals and Shape Reconstructioncited by 106
  19. 2021Ground-aware Monocular 3D Object Detection for Autonomous Drivingcited by 65
  20. 2019A*3D Dataset: Towards Autonomous Driving in Challenging Environmentscited by 64
  21. 2019Physics-Based Rendering for Improving Robustness to Raincited by 49
  22. 2017CURE-TSR: Challenging Unreal and Real Environments for Traffic Sign Recognitioncited by 32
  23. 2019Object-Centric Stereo Matching for 3D Object Detectioncited by 29
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  25. 2019Challenging Environments for Traffic Sign Detection: Reliability Assessment under Inclement Conditionscited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 5; 2023: 9; 2024: 5; 2025: 4; 2026: 3.

28 papers.

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  1. 2021The Norm Must Go On: Dynamic Unsupervised Domain Adaptation by Normalizationcited by 131
  2. 2022An Efficient Domain-Incremental Learning Approach to Drive in All Weather Conditionscited by 54
  3. 2022Benchmarking the Robustness of LiDAR-Camera Fusion for 3D Object Detectioncited by 49
  4. 2023Understanding the Robustness of 3D Object Detection with Bird's-Eye-View Representations in Autonomous Drivingcited by 37
  5. 2023Neuro-Modulated Hebbian Learning for Fully Test-Time Adaptationcited by 23
  6. 2023Survey on LiDAR Perception in Adverse Weather Conditionscited by 23
  7. 2022How Do We Fail? Stress Testing Perception in Autonomous Vehiclescited by 17
  8. 2024An Empirical Study of the Generalization Ability of Lidar 3D Object Detectors to Unseen Domainscited by 10
  9. 2025SAMFusion: Sensor-Adaptive Multimodal Fusion for 3D Object Detection in Adverse Weathercited by 10
  10. 2022Robust 3D Object Detection in Cold Weather Conditionscited by 7
  11. 2023Energy-based Detection of Adverse Weather Effects in LiDAR Datacited by 7
  12. 2024Learning Visual Conditioning Tokens to Correct Domain Shift for Fully Test-time Adaptationcited by 7
16 more
  1. 2022On the Robustness of 3D Object Detectorscited by 5
  2. 2023Radar Enlighten the Dark: Enhancing Low-Visibility Perception for Automated Vehicles with Camera-Radar Fusioncited by 4
  3. 2024Dual-Path Adversarial Lifting for Domain Shift Correction in Online Test-time Adaptationcited by 4
  4. 2023Benchmarking Robustness of AI-Enabled Multi-sensor Fusion Systems: Challenges and Opportunitiescited by 3
  5. 2024A Black-Box Evaluation Framework for Semantic Robustness in Bird's Eye View Detectioncited by 3
  6. 2021RiWNet: A moving object instance segmentation Network being Robust in adverse Weather conditionscited by 2
  7. 2023Towards Robust 3D Object Detection In Rainy Conditionscited by 2
  8. 2024Domain-Conditioned Transformer for Fully Test-time Adaptationcited by 2
  9. 2023Sit Back and Relax: Learning to Drive Incrementally in All Weather Conditionscited by 1
  10. 2025Enhanced 3D Object Detection via Diverse Feature Representations of 4D Radar Tensorcited by 1
  11. 2023DA-RAW: Domain Adaptive Object Detection for Real-World Adverse Weather Conditionscited by 0
  12. 2025A Multi-View High-Resolution Foot-Ankle Complex Point Cloud Dataset During Gait for Occlusion-Robust 3D Completioncited by 0
  13. 2025Progressive Conditioned Scale-Shift Recalibration of Self-Attention for Online Test-time Adaptationcited by 0
  14. 2026Enhancing Visual Perception in Foggy Conditions via Multiclass Fog Density Modelingcited by 0
  15. 2026Stereo 4D Radar for 3D Object Detection: Integrating Geometric Alignment and Absolute Velocity Estimationcited by 0
  16. 2026Beyond Benchmarks: Using VLMs to Reveal Systematic Classification Failures Under Real World Conditionscited by 0