mlsanityData to 14 Oct 2026

PixOOD: Pixel-Level Out-of-Distribution Detection

arXiv 2405.19882 ↗First posted 30 May 2024cs.CVcited by 20

Not on the map. Why?

Abstract (arXiv)

We propose a dense image prediction out-of-distribution detection algorithm, called PixOOD, which does not require training on samples of anomalous data and is not designed for a specific application which avoids traditional training biases. In order to model the complex intra-class variability of the in-distribution data at the pixel level, we propose an online data condensation algorithm which is more robust than standard K-means and is easily trainable through SGD. We evaluate PixOOD on a wide range of problems. It achieved state-of-the-art results on four out of seven datasets, while being competitive on the rest. The source code is available at https://github.com/vojirt/PixOOD.

Key facts. Cited by 20 papers in the map (data through 14 Oct 2026). Builds on 45 of its 57 references that are in the map. First posted on arXiv 30 May 2024.

Builds on

45 of 57 references.

References · 45

  1. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  2. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
  3. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
  4. 2023DINOv2: Learning Robust Visual Features without Supervisioncited by 7,974
  5. 2016Gaussian Error Linear Units (GELUs)cited by 3,502
  6. 2016A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networkscited by 2,385
  7. 2017Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networkscited by 1,328
  8. 2021Towards Total Recall in Industrial Anomaly Detectioncited by 776
  9. 2020PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localizationcited by 594
  10. 2021DRAEM -- A discriminatively trained reconstruction embedding for surface anomaly detectioncited by 514
  11. 2021CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing Flowscited by 321
  12. 2022A Unified Model for Multi-class Anomaly Detectioncited by 268
33 more
  1. 2023AnomalyGPT: Detecting Industrial Anomalies Using Large Vision-Language Modelscited by 171
  2. 2018IDD: A Dataset for Exploring Problems of Autonomous Navigation in Unconstrained Environmentscited by 163
  3. 2021SegmentMeIfYouCan: A Benchmark for Anomaly Segmentationcited by 150
  4. 2019Detecting the Unexpected via Image Resynthesiscited by 137
  5. 2020Entropy Maximization and Meta Classification for Out-Of-Distribution Detection in Semantic Segmentationcited by 133
  6. 2023CLIPN for Zero-Shot OOD Detection: Teaching CLIP to Say Nocited by 130
  7. 2019The Fishyscapes Benchmark: Measuring Blind Spots in Semantic Segmentationcited by 122
  8. 2016Lost and Found: Detecting Small Road Hazards for Self-Driving Vehiclescited by 117
  9. 2024FeatUp: A Model-Agnostic Framework for Features at Any Resolutioncited by 116
  10. 2024MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detectioncited by 113
  11. 2021Pixel-wise Anomaly Detection in Complex Driving Scenescited by 109
  12. 2021Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenescited by 83
  13. 2022PNI : Industrial Anomaly Detection using Position and Neighborhood Informationcited by 69
  14. 2022RbA: Segmenting Unknown Regions Rejected by Allcited by 67
  15. 2023Hierarchical Vector Quantized Transformer for Multi-class Unsupervised Anomaly Detectioncited by 66
  16. 2022Residual Pattern Learning for Pixel-wise Out-of-Distribution Detection in Semantic Segmentationcited by 55
  17. 2023Unmasking Anomalies in Road-Scene Segmentationcited by 45
  18. 2022DenseHybrid: Hybrid Anomaly Detection for Dense Open-set Recognitioncited by 42
  19. 2023On Advantages of Mask-level Recognition for Outlier-aware Segmentationcited by 42
  20. 2021Triggering Failures: Out-Of-Distribution detection by learning from local adversarial attacks in Semantic Segmentationcited by 40
  21. 2024Outlier detection by ensembling uncertainty with negative objectnesscited by 34
  22. 2021DKM: Differentiable K-Means Clustering Layer for Neural Network Compressioncited by 31
  23. 2020Detecting Road Obstacles by Erasing Themcited by 29
  24. 2021MODS -- A USV-oriented object detection and obstacle segmentation benchmarkcited by 27
  25. 2023LaRS: A Diverse Panoptic Maritime Obstacle Detection Dataset and Benchmarkcited by 19
  26. 2022Far Away in the Deep Space: Dense Nearest-Neighbor-Based Out-of-Distribution Detectioncited by 15
  27. 2023CSL: Class-Agnostic Structure-Constrained Learning for Segmentation Including the Unseencited by 15
  28. 2023ATTA: Anomaly-aware Test-Time Adaptation for Out-of-Distribution Detection in Segmentationcited by 14
  29. 2024IDD-X: A Multi-View Dataset for Ego-relative Important Object Localization and Explanation in Dense and Unstructured Trafficcited by 13
  30. 2023IDD-AW: A Benchmark for Safe and Robust Segmentation of Drive Scenes in Unstructured Traffic and Adverse Weathercited by 12
  31. 2021Dense Out-of-Distribution Detection by Robust Learning on Synthetic Negative Datacited by 10
  32. 2023A Discrepancy Aware Framework for Robust Anomaly Detectioncited by 9
  33. 2023Calibrated Out-of-Distribution Detection with a Generic Representationcited by 8

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 6; 2025: 7; 2026: 7.

20 papers.

Sort:

By area:

  1. 2024WildlifeReID-10k: Wildlife re-identification dataset with 10k individual animalscited by 19
  2. 2025Out-of-Distribution Segmentation in Autonomous Driving: Problems and State of the Artcited by 13
  3. 2024A Likelihood Ratio-Based Approach to Segmenting Unknown Objectscited by 12
  4. 2024The BRAVO Semantic Segmentation Challenge Results in UNCV2024cited by 6
  5. 2026AnomalyVFM -- Transforming Vision Foundation Models into Zero-Shot Anomaly Detectorscited by 4
  6. 2024Segment-Level Road Obstacle Detection Using Visual Foundation Model Priors and Likelihood Ratioscited by 3
  7. 2024Multi-Scale Foreground-Background Confidence for Out-of-Distribution Segmentationcited by 3
  8. 2025Uncertainty-Aware Likelihood Ratio Estimation for Pixel-Wise Out-of-Distribution Detectioncited by 3
  9. 2024Zero-shot Hazard Identification in Autonomous Driving: A Case Study on the COOOL Benchmarkcited by 2
  10. 2025A Dataset for Semantic Segmentation in the Presence of Unknownscited by 2
  11. 2025Out-of-Distribution Detection in LiDAR Semantic Segmentation Using Epistemic Uncertainty from Hierarchical GMMscited by 2
  12. 2025Open-set Anomaly Segmentation in Complex Scenarioscited by 1
8 more
  1. 2025Objectomaly: Objectness-Aware Refinement for OoD Segmentation with Structural Consistency and Boundary Precisioncited by 0
  2. 2025Training-Free Out-Of-Distribution Segmentation With Foundation Modelscited by 0
  3. 2026CURE-OOD: Benchmarking Out-of-Distribution Detection for Survival Predictioncited by 0
  4. 2026LARAD: Layout-Aware Road Anomaly Detection via Spatial-Logic Reasoningcited by 0
  5. 2026Towards Real-Time PixOOD: Efficient Anomaly Segmentation for Autonomous Vehiclescited by 0
  6. 2026Combining Foundation Model Confidence and Monocular Depth for Training-Free Out-of-Distribution Segmentationcited by 0
  7. 2026SAFe: Segment-guided Aggregation of Feature Densities for Anomaly-aware Segmentationcited by 0
  8. 2026Progressive Risk Estimation for Accident Anticipationcited by 0