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Out of Distribution (OOD) Detection

Out of Distribution (OOD) Detection is the task of detecting instances that do not belong to the distribution the classifier has been trained on. OOD data is often referred to as "unseen" data, as the model has not encountered it during training.

OOD detection is typically performed by training a model to distinguish between in-distribution (ID) data, which the model has seen during training, and OOD data, which it has not seen. This can be done using a variety of techniques, such as training a separate OOD detector, or modifying the model's architecture or loss function to make it more sensitive to OOD data.

Papers

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Showing 201–250 of 629 papers

TitleStatusHype
Score Combining for Contrastive OOD Detection—0
Hypercone Assisted Contour Generation for Out-of-Distribution Detection—0
A Closer Look at the Learnability of Out-of-Distribution (OOD) Detection—0
FARE: A Deep Learning-Based Framework for Radar-based Face Recognition and Out-of-distribution Detection—0
DisCoPatch: Taming Adversarially-driven Batch Statistics for Improved Out-of-Distribution Detection—0
ARES: Auxiliary Range Expansion for Outlier Synthesis—0
Harnessing Large Language and Vision-Language Models for Robust Out-of-Distribution Detection—0
Probabilistic Skip Connections for Deterministic Uncertainty Quantification in Deep Neural Networks—0
Multi-layer Radial Basis Function Networks for Out-of-distribution Detection—0
Overcoming Shortcut Problem in VLM for Robust Out-of-Distribution DetectionCode0
Dual Energy-Based Model with Open-World Uncertainty Estimation for Out-of-distribution Detection—0
Enhancing Reconstruction-Based Out-of-Distribution Detection in Brain MRI with Model and Metric EnsemblesCode0
Out-of-Distribution Detection with Prototypical Outlier ProxyCode0
Boosting LLM-based Relevance Modeling with Distribution-Aware Robust Learning—0
ITP: Instance-Aware Test Pruning for Out-of-Distribution DetectionCode0
Mining In-distribution Attributes in Outliers for Out-of-distribution DetectionCode0
Taylor Outlier ExposureCode0
EDGE: Unknown-aware Multi-label Learning by Energy Distribution Gap Expansion—0
Out-of-Distribution Detection with Overlap Index—0
Revisiting Energy-Based Model for Out-of-Distribution DetectionCode0
NCDD: Nearest Centroid Distance Deficit for Out-Of-Distribution Detection in Gastrointestinal VisionCode0
Enhancing Few-Shot Out-of-Distribution Detection with Gradient Aligned Context OptimizationCode0
Out-Of-Distribution Detection with Diversification (Provably)Code0
Non-Linear Outlier Synthesis for Out-of-Distribution DetectionCode0
Semantic or Covariate? A Study on the Intractable Case of Out-of-Distribution Detection—0
Going Beyond Conventional OOD DetectionCode0
Diffusion-based Layer-wise Semantic Reconstruction for Unsupervised Out-of-Distribution DetectionCode0
Double Descent Meets Out-of-Distribution Detection: Theoretical Insights and Empirical Analysis on the role of model complexity—0
MADOD: Generalizing OOD Detection to Unseen Domains via G-Invariance Meta-Learning—0
'No' Matters: Out-of-Distribution Detection in Multimodality Long Dialogue—0
Dimensionality-induced information loss of outliers in deep neural networks—0
Long-Tailed Out-of-Distribution Detection via Normalized Outlier Distribution AdaptationCode0
PViT: Prior-augmented Vision Transformer for Out-of-distribution DetectionCode0
What If the Input is Expanded in OOD Detection?Code0
GDDA: Semantic OOD Detection on Graphs under Covariate Shift via Score-Based Diffusion Models—0
LEGO-Learn: Label-Efficient Graph Open-Set LearningCode0
Adaptive Label Smoothing for Out-of-Distribution Detection—0
Tensor-Train Point Cloud Compression and Efficient Approximate Nearest-Neighbor Search—0
MetaOOD: Automatic Selection of OOD Detection Models—0
Unsupervised Hybrid framework for ANomaly Detection (HAND) -- applied to Screening MammogramCode0
Beyond Perceptual Distances: Rethinking Disparity Assessment for Out-of-Distribution Detection with Diffusion Models—0
Uncertainty-Guided Appearance-Motion Association Network for Out-of-Distribution Action DetectionCode0
Enhancing Outlier Knowledge for Few-Shot Out-of-Distribution Detection with Extensible Local Prompts—0
SOOD-ImageNet: a Large-Scale Dataset for Semantic Out-Of-Distribution Image Classification and Semantic SegmentationCode0
TagOOD: A Novel Approach to Out-of-Distribution Detection via Vision-Language Representations and Class Center LearningCode0
Diffusion based Semantic Outlier Generation via Nuisance Awareness for Out-of-Distribution Detection—0
Long-Tailed Out-of-Distribution Detection: Prioritizing Attention to TailCode0
Out-Of-Distribution Detection for Audio-visual Generalized Zero-Shot Learning: A General FrameworkCode0
Mitral Regurgitation Recognition based on Unsupervised Out-of-Distribution Detection with Residual Diffusion Amplification—0
Towards Open-World Object-based Anomaly Detection via Self-Supervised Outlier SynthesisCode0
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