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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 251–275 of 629 papers

TitleStatusHype
TTA-OOD: Test-time Augmentation for Improving Out-of-Distribution Detection in Gastrointestinal Vision—0
Improving Out-of-Distribution Detection by Combining Existing Post-hoc MethodsCode0
Enhancing OOD Detection Using Latent DiffusionCode0
SeTAR: Out-of-Distribution Detection with Selective Low-Rank ApproximationCode0
Exploiting Diffusion Prior for Out-of-Distribution Detection—0
Rethinking the Evaluation of Out-of-Distribution Detection: A Sorites ParadoxCode0
FOOD: Facial Authentication and Out-of-Distribution Detection with Short-Range FMCW Radar—0
Situation Monitor: Diversity-Driven Zero-Shot Out-of-Distribution Detection using Budding Ensemble Architecture for Object Detection—0
Can Dense Connectivity Benefit Outlier Detection? An Odyssey with NAS—0
Towards Out-of-Distribution Detection in Vocoder Recognition via Latent Feature Reconstruction—0
Effectiveness of Vision Language Models for Open-world Single Image Test Time Adaptation—0
When and How Does In-Distribution Label Help Out-of-Distribution Detection?Code0
WeiPer: OOD Detection using Weight Perturbations of Class Projections—0
Concept Matching with Agent for Out-of-Distribution DetectionCode0
Enhancing Near OOD Detection in Prompt Learning: Maximum Gains, Minimal Costs—0
Dual-Adapter: Training-free Dual Adaptation for Few-shot Out-of-Distribution Detection—0
Credal Wrapper of Model Averaging for Uncertainty Estimation in Classification—0
A Unified Approach Towards Active Learning and Out-of-Distribution Detection—0
Multi-Label Out-of-Distribution Detection with Spectral Normalized Joint EnergyCode0
Out-of-distribution detection based on subspace projection of high-dimensional features output by the last convolutional layerCode0
Language-Enhanced Latent Representations for Out-of-Distribution Detection in Autonomous Driving—0
Deep Metric Learning-Based Out-of-Distribution Detection with Synthetic Outlier Exposure—0
Feature Purified Transformer With Cross-level Feature Guiding Decoder For Multi-class OOD and Anomaly Deteciton—0
Out-of-distribution Detection in Medical Image Analysis: A survey—0
Gradient-Regularized Out-of-Distribution DetectionCode0
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