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Awesome-Out-Of-Distribution-Detection

A professionally curated list of papers, tutorials, books, videos, articles and open-source libraries etc for Out-of-distribution detection, robustness, and generalization
https://github.com/huytransformer/Awesome-Out-Of-Distribution-Detection

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Benchmarks
Libraries
OOD Detection
- CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances
- Energy-based Out-of-distribution Detection
- Likelihood Ratios for Out-of-Distribution Detection - FduW9ZWAR4) by Ren et al.
- Why ReLU Networks Yield High-Confidence Predictions Far Away From the Training Data and How to Mitigate the Problem - andr/relu_networks_overconfident) by Hein et al.
- (ODIN) Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks
- Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples
- A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks - detection) by Hendrycks and Gimpel
- CONJNORM: Tractable Density Estimation for Out-of-distribution Detection
- How To Overcome Curse-of-Dimensionality for Out-of-distribution Detection?
- Dream the Impossible: Outlier Imagination with Diffusion Models
- Non-Parametric Outlier Synthesis - wisc/npos) by Tao et al.
- Out-of-distribution Detection with Implicit Outlier Transformation
- Feed Two Birds with One Scone: Exploiting Wild Data for Both Out-of-Distribution Generalization and Detection - pLe638) by Bai et al.
- Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability - Mask) by Zhu et al
- READ: Aggregating Reconstruction Error into Out-of-Distribution Detection
- OpenOOD v1.5: Enhanced Benchmark for Out-of-distribution Detection
- Mitigating Neural Network Overconfidence with Logit Normalization
- Scaling Out-of-Distribution Detection for Real-World Settings - seg) by Hendrycks et al.
- (kNN) Out-of-Distribution Detection with Deep Nearest Neighbors - wisc/knn-ood) by Sun et al.
- Extremely Simple Activation Shaping for Out-of-Distribution Detection
- Igeood: An Information Geometry Approach to Out-of-Distribution Detection
- How to Exploit Hyperspherical Embeddings for Out-of-Distribution Detection? - wisc/cider) by Ming et al.
- VOS: Learning What You Don't Know by Virtual Outlier Synthesis - wisc/vos) by Du et al.
- DICE: Leveraging Sparsification for Out-of-Distribution Detection - wisc/dice) by Sun and Li
- On the Impact of Spurious Correlation for Out-of-distribution Detection - wisc/Spurious_OOD) by Ming et al.
- Provable Guarantees for Understanding Out-of-distribution Detection - OOD-Detection) by Morteza and Li
- MOS: Towards Scaling Out-of-distribution Detection for Large Semantic Space - wisc/large_scale_ood) by Huang and Li
- Single Layer Predictive Normalized Maximum Likelihood for Out-of-Distribution Detection
- ReAct: Out-of-distribution Detection With Rectified Activations - wisc/react) by Sun et al.
- ViM: Out-Of-Distribution with Virtual-logit Matching - l0p561in) by Wang et al.
- OpenOOD: Benchmarking Generalized Out-of-Distribution Detection
- Delving into Out-of-Distribution Detection with Vision-Language Representations - wisc/MCM) by Ming et al.
- (GradNorm) On the Importance of Gradients for Detecting Distributional Shifts in the Wild - wisc/gradnorm_ood) by Huang et al.
- Watermarking for Out-of-distribution Detection
- Can multi-label classification networks know what they don't know? - wisc/multi-label-ood) by Wang et al.
- SSD: A Unified Framework for Self-Supervised Outlier Detection - group/SSD) by Sehwag et al.
- Gradient-Regularized Out-of-Distribution Detection
- MultiOOD: Scaling Out-of-Distribution Detection for Multiple Modalities
- DIFFGUARD: Semantic Mismatch-Guided Out-of-Distribution Detection using Pre-trained Diffusion Models - lab/DiffGuard) by Gao et al.
- Understanding the Feature Norm for Out-of-Distribution Detection
- SAFE: Sensitivity-Aware Features for Out-of-Distribution Object Detection
- Residual Pattern Learning for Pixel-wise Out-of-Distribution Detection in Semantic Segmentation
- Simple and Effective Out-of-Distribution Detection via Cosine-based Softmax Loss
- Deep Feature Deblurring Diffusion for Detecting Out-of-Distribution Objects - OOD) by Wu et al.
- Revisit PCA-based technique for Out-of-Distribution Detection - GROUP/pca-based-out-of-distribution-detection) by Guan and Liu et al.
- WDiscOOD: Out-of-Distribution Detection via Whitened Linear Discriminant Analysis
- Anomaly Detection under Distribution Shift - lab/ADShift) by Cao et al.
- Out-of-Distribution Detection for Monocular Depth Estimation
- Unified Out-Of-Distribution Detection: A Model-Specific Perspective
- CLIPN for Zero-Shot OOD Detection: Teaching CLIP to Say No - lab/CLIPN) by Wang et al.
- A Constrained Bayesian Approach to Out-of-Distribution Prediction
- Why Out-of-Distribution Detection Experiments Are Not Reliable - Subtle Experimental Details Muddle the OOD Detector Rankings
- A Statistical Framework For Efficient Out-of-distribution Detection in Deep Neural Networks
- Variational- and Metric-based Deep Latent Space for Out-Of-Distribution Detection - CS-VIL/vmdls) by Dinari and Freifeld
- Out-of-Distribution Identification: Let Detector Tell Which I Am Not Sure
- Out-of-distribution Detection with Boundary Aware Learning
- Out-of-Distribution Detection with Semantic Mismatch under Masking - lab/MOODCat) by Yang et al.
- Data Invariants to Understand Unsupervised Out-of-Distribution Detection - invariants) by Doorenbos et al.
- Embedding contrastive unsupervised features to cluster in- and out-of-distribution noise in corrupted image datasets
- Sketching Curvature for Efficient Out-of-Distribution Detection for Deep Neural Networks
- Know Your Limits: Uncertainty Estimation with ReLU Classifiers Fails at Reliable OOD Detection - your-limits) by Ulmer and Cinà
- Density of States Estimation for Out of Distribution Detection
- WAIC, but Why? Generative Ensembles for Robust Anomaly Detection
- (NAP) Detection of Out-of-Distribution Samples Using Binary Neuron Activation Patterns - group/nap-ood) by Olber et al.
- VRA: Variational Rectified Activation for Out-of-distribution Detection
- GAIA: Delving into Gradient-based Attribution Abnormality for Out-of-distribution Detection
- CADet: Fully Self-supervised Anomaly Detection With Contrastive Learning - CADet) by Guille-Escuret et al.
- RoboDepth: Robust Out-of-distribution Depth Estimation Under Corruptions
- Diversify & Conquer: Outcome-directed Curriculum RL via Out-of-distribution Disagreement
- LoCoOp: Few-Shot Out-of-distribution Detection via Prompt Learning
- Decoupling MaxLogit for Out-of-Distribution Detection
- Balanced Energy Regularization Loss for Out-of-Distribution Detection
- Rethinking Out-of-Distribution (OOD) Detection: Masked Image Modeling Is All You Need
- Category-Extensible Out-of-distribution Detection via Hierarchical Context Descriptions
- Out-of-distribution Detection Learning With Unreliable Out-of-distribution Sources - group/ATOL) by Zheng and Wang et al.
- Dream the Impossible: Outlier Imagination with Diffusion Models
- Learning To Augment Distributions For Out-of-distribution Detection - group/DAL) by Wang et al.
- Nearest Neighbor Guidance for Out-of-Distribution Detection
- Distribution Shift Inversion for Out-of-Distribution Prediction - rp/Distribution-Shift-Iverson) by Yu et al.
- Uncertainty-Aware Optimal Transport for Semantically Coherent Out-of-Distribution Detection - OOD) by Lu et al.
- GEN: Pushing the Limits of Softmax-Based Out-of-Distribution Detection
- LINe: Out-of-Distribution Detection by Leveraging Important Neurons - Ahn/LINe-Out-of-Distribution-Detection-by-Leveraging-Important-Neurons) by Ahn et al.
- A Critical Analysis of Out-of-distribution Detection for Document Understanding
- A framework for benchmarking Class-out-of-distribution detection and its application to ImageNet
- Energy-based Out-of-Distribution Detection for Graph Neural Networks - GNNSafe) by Wu et al.
- The Tilted Variational Autoencoder: Improving Out-of-Distribution Detection
- Out-of-Distribution Detection based on In-Distribution Data Patterns Memorization with Modern Hopfield Energy
- Out-of-Distribution Detection and Selective Generation for Conditional Language Models
- Turning the Curse of Heterogeneity in Federated Learning into a Blessing for Out-of-Distribution Detection
- Non-Parametric Outlier Synthesis - wisc/npos) by Tao et al.
- Out-of-distribution Detection with Implicit Outlier Transformation
- Detecting Out-of-distribution Data through In-distribution Class Prior
- Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability - Mask) by Zhu et al
- In or Out? Fixing ImageNet Out-of-Distribution Detection Evaluation - cb/NINCO) by Bitterwolf et al.
- Unsupervised Out-of-Distribution Detection with Diffusion Inpainting
- Generative Causal Representation Learning for Out-of-Distribution Motion Forecasting
- READ: Aggregating Reconstruction Error into Out-of-Distribution Detection
- Model Ratatouille: Recycling Diverse Models for Out-of-Distribution Generalization
- Out-of-Distribution Generalization of Federated Learning via Implicit Invariant Relationships
- Concept-based Explanations for Out-of-Distribution Detectors
- Hybrid Energy Based Model in the Feature Space for Out-of-Distribution Detection
- Towards In-Distribution Compatible Out-of-Distribution Detection
- Robustness to Spurious Correlations Improves Semantic Out-of-Distribution Detection
- OpenOOD v1.5: Enhanced Benchmark for Out-of-distribution Detection
- Know Your Space: Inlier and Outlier Construction for Calibrating Medical OOD Detectors
- Linking Neural Collapse and L2 Normalization with Improved Out-of-Distribution Detection in Deep Neural Networks
- ViM: Out-Of-Distribution with Virtual-logit Matching - l0p561in) by Wang et al.
- Neural Mean Discrepancy for Efficient Out-of-Distribution Detection
- Deep Hybrid Models for Out-of-Distribution Detection
- Rethinking Reconstruction Autoencoder-Based Out-of-Distribution Detection
- Unknown-Aware Object Detection: Learning What You Don't Know from Videos in the Wild - wisc/stud) by Du et al.
- OpenOOD: Benchmarking Generalized Out-of-Distribution Detection
- Boosting Out-of-distribution Detection with Typical Features
- Your Out-of-Distribution Detection Method is Not Robust! - lab/ATD) by Azizmalayeri et al.
- Out-of-Distribution Detection with An Adaptive Likelihood Ratio on Informative Hierarchical VAE
- GOOD: A Graph Out-of-Distribution Benchmark
- GraphDE: A Generative Framework for Debiased Learning and Out-of-Distribution Detection on Graphs
- Is Out-of-Distribution Detection Learnable?
- Out-of-Distribution Detection via Conditional Kernel Independence Model
- Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment
- Delving into Out-of-Distribution Detection with Vision-Language Representations - wisc/MCM) by Ming et al.
- Beyond Mahalanobis Distance for Textual OOD Detection
- Density-driven Regularization for Out-of-distribution Detection
- SIREN: Shaping Representations for Detecting Out-of-Distribution Objects - wisc/siren) by Du et al.
- Mitigating Neural Network Overconfidence with Logit Normalization
- Scaling Out-of-Distribution Detection for Real-World Settings - seg) by Hendrycks et al.
- Open-Sampling: Exploring Out-of-Distribution data for Re-balancing Long-tailed datasets
- Model Agnostic Sample Reweighting for Out-of-Distribution Learning - zho14/MAPLE) by Zhou et al.
- Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition - science/long-tailed-ood-detection) by Wang et al.
- Breaking Down Out-of-Distribution Detection: Many Methods Based on OOD Training Data Estimate a Combination of the Same Core Quantities - cb/Breaking_Down_OOD_Detection) by Bitterwolf et al.
- Predicting Out-of-Distribution Error with the Projection Norm
- POEM: Out-of-Distribution Detection with Posterior Sampling - wisc/poem) by Ming et al.
- (kNN) Out-of-Distribution Detection with Deep Nearest Neighbors - wisc/knn-ood) by Sun et al.
- Training OOD Detectors in their Natural Habitats - Samuels et al.
- Extremely Simple Activation Shaping for Out-of-Distribution Detection
- MOS: Towards Scaling Out-of-distribution Detection for Large Semantic Space - wisc/large_scale_ood) by Huang and Li
- Single Layer Predictive Normalized Maximum Likelihood for Out-of-Distribution Detection
- STEP: Out-of-Distribution Detection in the Presence of Limited In-Distribution Labeled Data
- Revisiting flow generative models for Out-of-distribution detection
- PI3NN: Out-of-distribution-aware Prediction Intervals from Three Neural Networks
- (ATC) Leveraging unlabeled data to predict out-of-distribution performance
- Igeood: An Information Geometry Approach to Out-of-Distribution Detection
- How to Exploit Hyperspherical Embeddings for Out-of-Distribution Detection? - wisc/cider) by Ming et al.
- VOS: Learning What You Don't Know by Virtual Outlier Synthesis - wisc/vos) by Du et al.
- On the Impact of Spurious Correlation for Out-of-distribution Detection - wisc/Spurious_OOD) by Ming et al.
- iDECODe: In-Distribution Equivariance for Conformal Out-of-Distribution Detection
- Provable Guarantees for Understanding Out-of-distribution Detection - OOD-Detection) by Morteza and Li
- Learning Modular Structures That Generalize Out-of-Distribution (Student Abstract)
- Exploiting Mixed Unlabeled Data for Detecting Samples of Seen and Unseen Out-of-Distribution Classes
- Out-of-Distribution Detection Using Union of 1-Dimensional Subspaces
- MOOD: Multi-level Out-of-distribution Detection - wisc/MOOD) by Lin et al.
- Exploring the Limits of Out-of-Distribution Detection
- Learning Causal Semantic Representation for Out-of-Distribution Prediction - semantic-generative-model) by Liu et al.
- Towards optimally abstaining from prediction with OOD test examples
- Locally Most Powerful Bayesian Test for Out-of-Distribution Detection using Deep Generative Models
- RankFeat: Rank-1 Feature Removal for Out-of-distribution Detection
- ReAct: Out-of-distribution Detection With Rectified Activations - wisc/react) by Sun et al.
- (GradNorm) On the Importance of Gradients for Detecting Distributional Shifts in the Wild - wisc/gradnorm_ood) by Huang et al.
- Watermarking for Out-of-distribution Detection
- Can multi-label classification networks know what they don't know? - wisc/multi-label-ood) by Wang et al.
- SSD: A Unified Framework for Self-Supervised Outlier Detection - group/SSD) by Sehwag et al.
- Multiscale Score Matching for Out-of-Distribution Detection
- Understanding Failures in Out-of-Distribution Detection with Deep Generative Models
- Likelihood Ratios for Out-of-Distribution Detection - FduW9ZWAR4) by Ren et al.
- Unsupervised Out-of-Distribution Detection by Maximum Classifier Discrepancy - Out-of-Distribution-Detection-by-Maximum-Classifier-Discrepancy) by Yu and Aizawa
- (Mahalanobis) A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks
- Semantically Coherent Out-of-Distribution Detection
- CODEs: Chamfer Out-of-Distribution Examples against Overconfidence Issue
- DICE: Leveraging Sparsification for Out-of-Distribution Detection - wisc/dice) by Sun and Li
- Deep Residual Flow for Out of Distribution Detection - Flow) by Zisselman and Tamar
- Generalized ODIN: Detecting Out-of-Distribution Image Without Learning From Out-of-Distribution Data - ODIN-TF) by Hsu et al.
- CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances
- Energy-based Out-of-distribution Detection
- OOD-MAML: Meta-Learning for Few-Shot Out-of-Distribution Detection and Classification - metalearning-for-fewshot-outofdistribution-detection-and-classification) by Jeong and Kim
- Towards Maximizing the Representation Gap between In-Domain & Out-of-Distribution Examples - representation-gap) by Nandy et al.
- Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder - Regret) by Xiao et al.
- Why Normalizing Flows Fail to Detect Out-of-Distribution Data
- Towards Neural Networks That Provably Know When They Don't Know - certain-uncertainty) by Meinke et al.
- Detecting Out-of-Distribution Examples with Gram Matrices - ood-detection) by Sastry and Oore
- Out-Of-Distribution Detection for Generalized Zero-Shot Action Recognition - od) by Mandal et al.
- Out-of-Distribution Detection using Multiple Semantic Label Representations
- Why ReLU Networks Yield High-Confidence Predictions Far Away From the Training Data and How to Mitigate the Problem - andr/relu_networks_overconfident) by Hein et al.
- Do Deep Generative Models Know What They Don't Know? - Topics-in-Machine-Learning-and-Data-Science/Jia.pdf) by Nalisnick et al.
- (OE) Deep Anomaly Detection with Outlier Exposure - exposure) by Hendrycks et al.
- (ODIN) Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks
- Training Confidence-calibrated Classifiers for Detecting Out-of-Distribution Samples
- Out-of-Distribution Detection Using an Ensemble of Self-Supervised Leave-out Classifiers - of-Leave-out-Classifiers) by Vyas et al.
- Learning Confidence for Out-of-Distribution Detection in Neural Networks - mlrg/confidence_estimation) by DeVries and Taylor
- A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks - detection) by Hendrycks and Gimpel
- Taming False Positives in Out-of-Distribution Detection with Human Feedback - OOD) by Vishwakarma et al.
- OODRobustBench: a Benchmark and Large-Scale Analysis of Adversarial Robustness under Distribution Shift
- A Geometric Explanation of the Likelihood OOD Detection Paradox - labs/dgm_ood_detection) by Kamkari et al.
- ODIM: Outlier Detection via Likelihood of Under-Fitted Generative Models
- A Provable Decision Rule for Out-of-Distribution Detection
- When and How Does In-Distribution Label Help Out-of-Distribution Detection? - wisc/id_label) by Du et al.
- Graph Out-of-Distribution Detection Goes Neighborhood Shaping
- Out-of-Distribution Detection via Deep Multi-Comprehension Ensemble
- Bounded and Uniform Energy-based Out-of-distribution Detection for Graphs - Bounded-and-Uniform-Energy-based-Out-of-distribution-Detection-for-Graphs) by Yang et al.
- DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection
- Envisioning Outlier Exposure by Large Language Models for Out-of-Distribution Detection - group/EOE) by Cao et al.
- Prometheus: Out-of-distribution Fluid Dynamics Modeling with Disentangled Graph ODE
- Optimal Ridge Regularization for Out-of-Distribution Prediction - ridge) by Patil et al.
- Long-Tailed Anomaly Detection with Learnable Class Names
- Enhancing the Power of OOD Detection via Sample-Aware Model Selection
- Test-Time Linear Out-of-Distribution Detection
- ID-like Prompt Learning for Few-Shot Out-of-Distribution Detection - like) by Bai et al.
- YolOOD: Utilizing Object Detection Concepts for Multi-Label Out-of-Distribution Detection
- Learning Transferable Negative Prompts for Out-of-Distribution Detection - lab/negprompt) by Li et al.
- A Noisy Elephant in the Room: Is Your Out-of-Distribution Detector Robust to Label Noise? - labelnoise) by Humblot-Renaux et al.
- Discriminability-Driven Channel Selection for Out-of-Distribution Detection
- CORES: Convolutional Response-based Score for Out-of-distribution Detection
- Towards In-Distribution Compatible Out-of-Distribution Detection
- In- or Out-of-Distribution Detection via Dual Divergence Estimation
- Detecting Out-Of-Distribution Samples Via Conditional Distribution Entropy With Optimal Transport
- CONJNORM: Tractable Density Estimation for Out-of-distribution Detection
- Learning With Mixture Of Prototypes For Out-Of-Distribution Detection
- How Does Unlabled Data Provably Help Out-Of-Distribution Detection? - wisc/sal) by Du and Fang et al.
- HYPO: Hyperspherical Out-Of-Distribution Generalization - wisc/hypo) by Bai and Ming et al.
- ImageNet-OOD: Deciphering Modern Out-Of-Distribution Detection Algorithms
- Towards Optimal Feature-Shaping Methods For Out-Of-Distribution Detection
- Out-Of-Distribution Detection With Negative Prompts
- DOS: Diverse Outlier Sampling For Out-Of-Distribution Detection
- NECO: Neural Collapse Based Out-Of-Distribution Detection
- Plugin Estimators For Selective Classification With Out-Of-Distribution Detection
- Image Background Servers As Good Proxy For Out-Of-Distribution Data
- Out-Of-Distribution Detection By Leveraging Between-Layer Transformation Smoothness
- Scaling For Training-Time and Posthoc Out-Of-Distribution Detection Enhancement
- Neuron Activation Coverage: Rethinking Out-Of-Distribution Detection and Generalization
- How To Overcome Curse-of-Dimensionality for Out-of-distribution Detection?
- RoboDepth: Robust Out-Of-Distribution Depth Estimation under Corruptions
- GradOrth: A Simple Yet Efficient Out-of-distribution Detection with Orthogonal Projection of Gradients
- Characterizing Out-of-distribution Error via Optimal Transport
- On the Importancce of Feature Separability in Predicting Out-of-distribution Error
- ATTA: Anomaly-aware Test-Time Adaptation for Out-of-distribution Detection in Segmentation
- Diversified Outlier Exposure for Out-of-distribution Detection via Informative Extrapolation - group/DivOE) by Zhu et al.
- Optimal Parameter and Neuron Pruning for Out-of-distribution Detection
- GalLoP: Learning Global and Local Prompts for Vision-Language Models
- OODRobustBench: a Benchmark and Large-Scale Analysis of Adversarial Robustness under Distribution Shift
- RankFeat: Rank-1 Feature Removal for Out-of-distribution Detection
OOD Everything else
OOD Generalization
OOD Robustness
Table of Contents

Programming Languages

Python 5 Jupyter Notebook 2

Categories

OOD Detection 239 OOD Generalization 54 OOD Everything else 30 Table of Contents 14 OOD Robustness 13 Libraries 11 Benchmarks 8

Sub Categories

Keywords

open-set-recognition 3 ood-detection 3 anomaly-detection 2 novelty-detection 2 out-of-distribution-detection 2 robustness 2 image-classification 1 aleatoric-uncertainty 1 label-noise 1 depth-estimation 1 autonomous-driving 1 noisy-labels 1 outlier-detection 1 confidence-estimation 1 deep-learning 1 neural-network 1 pytorch 1