mlsanityData to 7 Oct 2026

Towards Safe Autonomous Driving: Capture Uncertainty in the Deep Neural Network For Lidar 3D Vehicle Detection

arXiv 1804.05132 ↗First posted 13 Apr 2018cs.RO cs.CVcited by 82

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Abstract (arXiv)

To assure that an autonomous car is driving safely on public roads, its object detection module should not only work correctly, but show its prediction confidence as well. Previous object detectors driven by deep learning do not explicitly model uncertainties in the neural network. We tackle with this problem by presenting practical methods to capture uncertainties in a 3D vehicle detector for Lidar point clouds. The proposed probabilistic detector represents reliable epistemic uncertainty and aleatoric uncertainty in classification and localization tasks. Experimental results show that the epistemic uncertainty is related to the detection accuracy, whereas the aleatoric uncertainty is influenced by vehicle distance and occlusion. The results also show that we can improve the detection performance by 1%-5% by modeling the aleatoric uncertainty.

Key facts. Cited by 82 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Apr 2018.

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Citing papers per year: 2019: 1; 2020: 1; 2021: 18; 2022: 17; 2023: 16; 2024: 14; 2025: 6; 2026: 9.

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  1. 2021A Survey of Uncertainty in Deep Neural Networkscited by 675
  2. 2021Active Learning for Deep Object Detection via Probabilistic Modelingcited by 79
  3. 2023Uncertainty Estimation by Fisher Information-based Evidential Deep Learningcited by 58
  4. 2022Uncertainty Quantification of Collaborative Detection for Self-Drivingcited by 46
  5. 2024DME-Driver: Integrating Human Decision Logic and 3D Scene Perception in Autonomous Drivingcited by 41
  6. 2021Estimating and Evaluating Regression Predictive Uncertainty in Deep Object Detectorscited by 37
  7. 2021CFC-Net: A Critical Feature Capturing Network for Arbitrary-Oriented Object Detection in Remote Sensing Imagescited by 29
  8. 2021Uncertainty for Identifying Open-Set Errors in Visual Object Detectioncited by 26
  9. 2022GLENet: Boosting 3D Object Detectors with Generative Label Uncertainty Estimationcited by 24
  10. 2023Unsupervised Self-Driving Attention Prediction via Uncertainty Mining and Knowledge Embeddingcited by 19
  11. 2021Collaborative Uncertainty in Multi-Agent Trajectory Forecastingcited by 17
  12. 2022Out-of-Distribution Detection for LiDAR-based 3D Object Detectioncited by 17
38 more
  1. 2025Evaluating Uncertainty and Quality of Vision-Language-Action-enabled Robotscited by 17
  2. 2021CertainNet: Sampling-free Uncertainty Estimation for Object Detectioncited by 15
  3. 2022STUN: Self-Teaching Uncertainty Estimation for Place Recognitioncited by 13
  4. 2022Collaborative Uncertainty Benefits Multi-Agent Multi-Modal Trajectory Forecastingcited by 13
  5. 2019Gaze Training by Modulated Dropout Improves Imitation Learningcited by 10
  6. 2021Prediction Surface Uncertainty Quantification in Object Detection Models for Autonomous Drivingcited by 10
  7. 2022Uncertainty Estimation for Multi-view Data: The Power of Seeing the Whole Picturecited by 10
  8. 2021A Review of Testing Object-Based Environment Perception for Safe Automated Drivingcited by 9
  9. 2022GaIA: Graphical Information Gain based Attention Network for Weakly Supervised Point Cloud Semantic Segmentationcited by 9
  10. 2024Posterior Uncertainty Quantification in Neural Networks using Data Augmentationcited by 9
  11. 2020Driving Through Ghosts: Behavioral Cloning with False Positivescited by 8
  12. 2022Evaluating Object (mis)Detection from a Safety and Reliability Perspective: Discussion and Measurescited by 8
  13. 2024SURE: SUrvey REcipes for building reliable and robust deep networkscited by 8
  14. 2022Reducing Overconfidence Predictions for Autonomous Driving Perceptioncited by 7
  15. 2023LS-VOS: Identifying Outliers in 3D Object Detections Using Latent Space Virtual Outlier Synthesiscited by 7
  16. 2024Training Bayesian Neural Networks with Sparse Subspace Variational Inferencecited by 7
  17. 2024Uncertainty-boosted Robust Video Activity Anticipationcited by 7
  18. 2021Giving Commands to a Self-Driving Car: How to Deal with Uncertain Situations?cited by 6
  19. 2023Deep Anti-Regularized Ensembles provide reliable out-of-distribution uncertainty quantificationcited by 6
  20. 2023Uncertainty-Encoded Multi-Modal Fusion for Robust Object Detection in Autonomous Drivingcited by 6
  21. 2025Uncertainty-Aware Online Extrinsic Calibration: A Conformal Prediction Approachcited by 6
  22. 2022LiDAR-MIMO: Efficient Uncertainty Estimation for LiDAR-based 3D Object Detectioncited by 5
  23. 2023Overcoming the Limitations of Localization Uncertainty: Efficient & Exact Non-Linear Post-Processing and Calibrationcited by 5
  24. 2022On Attacking Out-Domain Uncertainty Estimation in Deep Neural Networkscited by 4
  25. 2021Probabilistic Approach for Road-Users Detectioncited by 3
  26. 2022An Exploratory Study of AI System Risk Assessment from the Lens of Data Distribution and Uncertaintycited by 3
  27. 2022Key Feature Replacement of In-Distribution Samples for Out-of-Distribution Detectioncited by 3
  28. 2023Uncertainty-Aware AB3DMOT by Variational 3D Object Detectioncited by 3
  29. 2023Pedestrian Trajectory Forecasting Using Deep Ensembles Under Sensing Uncertaintycited by 3
  30. 2023LMD: Light-weight Prediction Quality Estimation for Object Detection in Lidar Point Cloudscited by 3
  31. 2024Run-time Monitoring of 3D Object Detection in Automated Driving Systems Using Early Layer Neural Activation Patternscited by 3
  32. 2021AI perspectives in Smart Cities and Communities to enable road vehicle automation and smart traffic controlcited by 2
  33. 2021False Positive Detection and Prediction Quality Estimation for LiDAR Point Cloud Segmentationcited by 2
  34. 2022Uncertainty-Aware Lidar Place Recognition in Novel Environmentscited by 2
  35. 2022Augmentation by Counterfactual Explanation -- Fixing an Overconfident Classifiercited by 2
  36. 2023Informative Data Selection with Uncertainty for Multi-modal Object Detectioncited by 2
  37. 2023Training of Neural Networks with Uncertain Data: A Mixture of Experts Approachcited by 2
  38. 2021From a Point Cloud to a Simulation Model: Bayesian Segmentation and Entropy based Uncertainty Estimation for 3D Modellingcited by 1

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