mlsanityData to 7 Oct 2026

OpenOOD: Benchmarking Generalized Out-of-Distribution Detection

arXiv 2210.07242 ↗First posted 13 Oct 2022cs.CV cs.AI cs.LGcited by 267

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Abstract (arXiv)

Out-of-distribution (OOD) detection is vital to safety-critical machine learning applications and has thus been extensively studied, with a plethora of methods developed in the literature. However, the field currently lacks a unified, strictly formulated, and comprehensive benchmark, which often results in unfair comparisons and inconclusive results. From the problem setting perspective, OOD detection is closely related to neighboring fields including anomaly detection (AD), open set recognition (OSR), and model uncertainty, since methods developed for one domain are often applicable to each other. To help the community to improve the evaluation and advance, we build a unified, well-structured codebase called OpenOOD, which implements over 30 methods developed in relevant fields and provides a comprehensive benchmark under the recently proposed generalized OOD detection framework. With a comprehensive comparison of these methods, we are gratified that the field has progressed significantly over the past few years, where both preprocessing methods and the orthogonal post-hoc methods show strong potential.

Key facts. Cited by 267 papers in the map (data through 7 Oct 2026). Builds on 59 of its 85 references that are in the map. First posted on arXiv 13 Oct 2022.

Builds on

59 of 85 references.

References · 59

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38 more
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50 most cited of 59 All 59 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 8; 2023: 67; 2024: 65; 2025: 81; 2026: 46.

267 papers.

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  1. 2023OpenOOD v1.5: Enhanced Benchmark for Out-of-Distribution Detectioncited by 178
  2. 2023In or Out? Fixing ImageNet Out-of-Distribution Detection Evaluationcited by 132
  3. 2023LoCoOp: Few-Shot Out-of-Distribution Detection via Prompt Learningcited by 107
  4. 2024TFG: Unified Training-Free Guidance for Diffusion Modelscited by 103
  5. 2023BMAD: Benchmarks for Medical Anomaly Detectioncited by 81
  6. 2023Dream the Impossible: Outlier Imagination with Diffusion Modelscited by 77
  7. 2023Scaling for Training Time and Post-hoc Out-of-distribution Detection Enhancementcited by 77
  8. 2022GLUE-X: Evaluating Natural Language Understanding Models from an Out-of-distribution Generalization Perspectivecited by 72
  9. 2023Nearest Neighbor Guidance for Out-of-Distribution Detectioncited by 64
  10. 2023SoTTA: Robust Test-Time Adaptation on Noisy Data Streamscited by 63
  11. 2024Learning with Mixture of Prototypes for Out-of-Distribution Detectioncited by 43
  12. 2023You Can Ground Earlier than See: An Effective and Efficient Pipeline for Temporal Sentence Grounding in Compressed Videoscited by 41
38 more
  1. 2023Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolationcited by 38
  2. 2023GL-MCM: Global and Local Maximum Concept Matching for Zero-Shot Out-of-Distribution Detectioncited by 36
  3. 2024How Does Unlabeled Data Provably Help Out-of-Distribution Detection?cited by 36
  4. 2024Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods?cited by 34
  5. 2023Continuous Learning for Android Malware Detectioncited by 33
  6. 2023A Survey on Out-of-Distribution Detection in NLPcited by 31
  7. 2024COME: Test-time adaption by Conservatively Minimizing Entropycited by 31
  8. 2022Block Selection Method for Using Feature Norm in Out-of-distribution Detectioncited by 30
  9. 2025Mahalanobis++: Improving OOD Detection via Feature Normalizationcited by 30
  10. 2023Neuron Activation Coverage: Rethinking Out-of-distribution Detection and Generalizationcited by 28
  11. 2024MultiOOD: Scaling Out-of-Distribution Detection for Multiple Modalitiescited by 28
  12. 2025Bridging the Vision-Brain Gap with an Uncertainty-Aware Blur Priorcited by 28
  13. 2023DiffGuard: Semantic Mismatch-Guided Out-of-Distribution Detection using Pre-trained Diffusion Modelscited by 25
  14. 2023Understanding the Feature Norm for Out-of-Distribution Detectioncited by 25
  15. 2023DIVERSIFY: A General Framework for Time Series Out-of-distribution Detection and Generalizationcited by 24
  16. 2023Reliability in Semantic Segmentation: Can We Use Synthetic Data?cited by 24
  17. 2024Out-of-Distribution Detection with a Single Unconditional Diffusion Modelcited by 22
  18. 2024LAPT: Label-driven Automated Prompt Tuning for OOD Detection with Vision-Language Modelscited by 21
  19. 2025Franca: Nested Matryoshka Clustering for Scalable Visual Representation Learningcited by 21
  20. 2023SCT: A Simple Baseline for Parameter-Efficient Fine-Tuning via Salient Channelscited by 20
  21. 2023Sensitivity-Aware Amortized Bayesian Inferencecited by 20
  22. 2024Robust Semi-supervised Learning by Wisely Leveraging Open-set Datacited by 20
  23. 2023Diversifying Spatial-Temporal Perception for Video Domain Generalizationcited by 19
  24. 2025Secure On-Device Video OOD Detection Without Backpropagationcited by 19
  25. 2024Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmarkcited by 18
  26. 2023Class Incremental Learning via Likelihood Ratio Based Task Predictioncited by 17
  27. 2024Structure-based out-of-distribution (OOD) materials property prediction: a benchmark studycited by 17
  28. 2023Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capabilitycited by 16
  29. 2024MetaOOD: Automatic Selection of OOD Detection Modelscited by 16
  30. 2024AdaNeg: Adaptive Negative Proxy Guided OOD Detection with Vision-Language Modelscited by 16
  31. 2022Far Away in the Deep Space: Dense Nearest-Neighbor-Based Out-of-Distribution Detectioncited by 15
  32. 2023VRA: Variational Rectified Activation for Out-of-distribution Detectioncited by 15
  33. 2023Average of Pruning: Improving Performance and Stability of Out-of-Distribution Detectioncited by 14
  34. 2023Towards Trustworthy Dataset Distillationcited by 14
  35. 2025Out-of-Distribution Detection Methods Answer the Wrong Questionscited by 14
  36. 2024A noisy elephant in the room: Is your out-of-distribution detector robust to label noise?cited by 13
  37. 2024Dissecting Out-of-Distribution Detection and Open-Set Recognition: A Critical Analysis of Methods and Benchmarkscited by 13
  38. 2025OpenMIBOOD: Open Medical Imaging Benchmarks for Out-Of-Distribution Detectioncited by 13

50 most cited of 267 All 267 (JSON)