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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

Showing 251300 of 629 papers

TitleStatusHype
TTA-OOD: Test-time Augmentation for Improving Out-of-Distribution Detection in Gastrointestinal Vision0
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 Detection0
Rethinking the Evaluation of Out-of-Distribution Detection: A Sorites ParadoxCode0
FOOD: Facial Authentication and Out-of-Distribution Detection with Short-Range FMCW Radar0
Situation Monitor: Diversity-Driven Zero-Shot Out-of-Distribution Detection using Budding Ensemble Architecture for Object Detection0
Towards Out-of-Distribution Detection in Vocoder Recognition via Latent Feature Reconstruction0
Can Dense Connectivity Benefit Outlier Detection? An Odyssey with NAS0
Effectiveness of Vision Language Models for Open-world Single Image Test Time Adaptation0
When and How Does In-Distribution Label Help Out-of-Distribution Detection?Code0
WeiPer: OOD Detection using Weight Perturbations of Class Projections0
Concept Matching with Agent for Out-of-Distribution DetectionCode0
Enhancing Near OOD Detection in Prompt Learning: Maximum Gains, Minimal Costs0
Dual-Adapter: Training-free Dual Adaptation for Few-shot Out-of-Distribution Detection0
Credal Wrapper of Model Averaging for Uncertainty Estimation in Classification0
A Unified Approach Towards Active Learning and Out-of-Distribution Detection0
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 Driving0
Deep Metric Learning-Based Out-of-Distribution Detection with Synthetic Outlier Exposure0
Feature Purified Transformer With Cross-level Feature Guiding Decoder For Multi-class OOD and Anomaly Deteciton0
Out-of-distribution Detection in Medical Image Analysis: A survey0
Gradient-Regularized Out-of-Distribution DetectionCode0
Rethinking Out-of-Distribution Detection for Reinforcement Learning: Advancing Methods for Evaluation and DetectionCode0
VI-OOD: A Unified Representation Learning Framework for Textual Out-of-distribution DetectionCode0
On the Learnability of Out-of-distribution Detection0
Your Finetuned Large Language Model is Already a Powerful Out-of-distribution Detector0
A noisy elephant in the room: Is your out-of-distribution detector robust to label noise?Code0
Weak Distribution Detectors Lead to Stronger Generalizability of Vision-Language Prompt TuningCode0
BAM: Box Abstraction Monitors for Real-time OoD Detection in Object Detection0
Hyperbolic Metric Learning for Visual Outlier Detection0
Out-of-Distribution Detection Using Peer-Class Generated by Large Language Model0
Out-of-Distribution Detection Should Use Conformal Prediction (and Vice-versa?)0
Enhancing Out-of-Distribution Detection with Multitesting-based Layer-wise Feature Fusion0
Energy Correction Model in the Feature Space for Out-of-Distribution Detection0
COOD: Combined out-of-distribution detection using multiple measures for anomaly & novel class detection in large-scale hierarchical classification0
Out-of-distribution Partial Label Learning0
Approximations to the Fisher Information Metric of Deep Generative Models for Out-Of-Distribution DetectionCode0
ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection0
Trustworthy Personalized Bayesian Federated Learning via Posterior Fine-Tune0
Understanding Likelihood of Normalizing Flow and Image Complexity through the Lens of Out-of-Distribution Detection0
Out-of-Distribution Detection and Data Drift Monitoring using Statistical Process Control0
Feature Density Estimation for Out-of-Distribution Detection via Normalizing Flows0
Kernel PCA for Out-of-Distribution DetectionCode0
Zero-shot Object-Level OOD Detection with Context-Aware Inpainting0
Comprehensive OOD Detection Improvements0
NODI: Out-Of-Distribution Detection with Noise from Diffusion0
UFO: Unidentified Foreground Object Detection in 3D Point Cloud0
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