mlsanityData to 7 Oct 2026

Efficient Uncertainty Estimation for Semantic Segmentation in Videos

arXiv 1807.11037 ↗First posted 29 Jul 2018cs.CVcited by 46

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Abstract (arXiv)

Uncertainty estimation in deep learning becomes more important recently. A deep learning model can't be applied in real applications if we don't know whether the model is certain about the decision or not. Some literature proposes the Bayesian neural network which can estimate the uncertainty by Monte Carlo Dropout (MC dropout). However, MC dropout needs to forward the model N times which results in N times slower. For real-time applications such as a self-driving car system, which needs to obtain the prediction and the uncertainty as fast as possible, so that MC dropout becomes impractical. In this work, we propose the region-based temporal aggregation (RTA) method which leverages the temporal information in videos to simulate the sampling procedure. Our RTA method with Tiramisu backbone is 10x faster than the MC dropout with Tiramisu backbone (N=5). Furthermore, the uncertainty estimation obtained by our RTA method is comparable to MC dropout's uncertainty estimation on pixel-level and frame-level metrics.

Key facts. Cited by 46 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 Jul 2018.

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Citing papers per year: 2021: 10; 2022: 12; 2023: 7; 2024: 9; 2025: 5; 2026: 3.

46 papers.

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  1. 2021A Survey on Deep Learning Technique for Video Segmentationcited by 132
  2. 2024NeRF On-the-go: Exploiting Uncertainty for Distractor-free NeRFs in the Wildcited by 85
  3. 2021Learning Probabilistic Ordinal Embeddings for Uncertainty-Aware Regressioncited by 58
  4. 2021Semantics for Robotic Mapping, Perception and Interaction: A Surveycited by 56
  5. 2021Corner Cases for Visual Perception in Automated Driving: Some Guidance on Detection Approachescited by 27
  6. 2021A Survey on Epistemic (Model) Uncertainty in Supervised Learning: Recent Advances and Applicationscited by 24
  7. 2021Domain Adaptive Video Segmentation via Temporal Consistency Regularizationcited by 21
  8. 2025Toward Real-world BEV Perception: Depth Uncertainty Estimation via Gaussian Splattingcited by 20
  9. 2022Semantic-SuPer: A Semantic-aware Surgical Perception Framework for Endoscopic Tissue Identification, Reconstruction, and Trackingcited by 19
  10. 2024RankED: Addressing Imbalance and Uncertainty in Edge Detection Using Ranking-based Lossescited by 18
  11. 2022Uncertainty-aware Panoptic Segmentationcited by 17
  12. 2021Robust Monocular Localization in Sparse HD Maps Leveraging Multi-Task Uncertainty Estimationcited by 11
34 more
  1. 2022Domain Adaptive Video Segmentation via Temporal Pseudo Supervisioncited by 11
  2. 2021Trust It or Not: Confidence-Guided Automatic Radiology Report Generationcited by 9
  3. 2023Multi-view 3D Object Reconstruction and Uncertainty Modelling with Neural Shape Priorcited by 9
  4. 2024Trustworthy Multimodal Fusion for Sentiment Analysis in Ordinal Sentiment Spacecited by 8
  5. 2023Temporal-aware Hierarchical Mask Classification for Video Semantic Segmentationcited by 7
  6. 2024A Unified Approach Towards Active Learning and Out-of-Distribution Detectioncited by 7
  7. 2022Uncertainty-aware LiDAR Panoptic Segmentationcited by 6
  8. 2023Stream-based Active Learning by Exploiting Temporal Properties in Perception with Temporal Predicted Losscited by 6
  9. 2024A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentationcited by 6
  10. 2025Joint Out-of-Distribution Filtering and Data Discovery Active Learningcited by 6
  11. 2026Video Understanding: From Geometry and Semantics to Unified Modelscited by 5
  12. 2022Multimodal Detection of Unknown Objects on Roads for Autonomous Drivingcited by 4
  13. 2022Uncertainty in Real-Time Semantic Segmentation on Embedded Systemscited by 3
  14. 2023Motion-state Alignment for Video Semantic Segmentationcited by 3
  15. 2024Safety Monitoring of Machine Learning Perception Functions: a Surveycited by 3
  16. 2026Bootstrapping Video Semantic Segmentation Model via Distillation-assisted Test-Time Adaptationcited by 3
  17. 2022FoV-Net: Field-of-View Extrapolation Using Self-Attention and Uncertaintycited by 2
  18. 2022Quantifying Model Uncertainty for Semantic Segmentation using Operators in the RKHScited by 2
  19. 2022Learning Implicit Functions for Dense 3D Shape Correspondence of Generic Objectscited by 2
  20. 2023A Metacognitive Approach to Out-of-Distribution Detection for Segmentationcited by 2
  21. 2025A Comprehensive Survey on Video Scene Parsing:Advances, Challenges, and Prospectscited by 2
  22. 2025TPA: Temporal Prompt Alignment for Fetal Congenital Heart Defect Classificationcited by 2
  23. 2021Neighborhood Spatial Aggregation MC Dropout for Efficient Uncertainty-aware Semantic Segmentation in Point Cloudscited by 1
  24. 2023Uncertainty estimation in Deep Learning for Panoptic segmentationcited by 1
  25. 2024Road Obstacle Detection based on Unknown Objectness Scorescited by 1
  26. 2025UAGLNet: Uncertainty-Aggregated Global-Local Fusion Network with Cooperative CNN-Transformer for Building Extractioncited by 1
  27. 2021Deep few-shot learning for bi-temporal building change detectioncited by 0
  28. 2022Deep Learning Model with GA based Feature Selection and Context Integrationcited by 0
  29. 2022Representation Recycling for Streaming Video Analysiscited by 0
  30. 2022SA-NET.v2: Real-time vehicle detection from oblique UAV images with use of uncertainty estimation in deep meta-learningcited by 0
  31. 2023Adaptive Scheduling for Edge-Assisted DNN Servingcited by 0
  32. 2024Uncertainty-aware Human Mobility Modeling and Anomaly Detectioncited by 0
  33. 2024Breaking The Ice: Video Segmentation for Close-Range Ice-Covered Waterscited by 0
  34. 2026U-SEG: Uncertainty in SEGmentation -- A systematic multi-variable explorationcited by 0