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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 151200 of 629 papers

TitleStatusHype
Learning Transferable Negative Prompts for Out-of-Distribution DetectionCode2
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
Negative Label Guided OOD Detection with Pretrained Vision-Language ModelsCode1
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
Learning with Mixture of Prototypes for Out-of-Distribution DetectionCode1
Kernel PCA for Out-of-Distribution DetectionCode0
Zero-shot Object-Level OOD Detection with Context-Aware Inpainting0
Towards Optimal Feature-Shaping Methods for Out-of-Distribution DetectionCode1
Comprehensive OOD Detection Improvements0
NODI: Out-Of-Distribution Detection with Noise from Diffusion0
Rethinking Test-time Likelihood: The Likelihood Path Principle and Its Application to OOD DetectionCode2
UFO: Unidentified Foreground Object Detection in 3D Point Cloud0
MOODv2: Masked Image Modeling for Out-of-Distribution DetectionCode2
EPA: Neural Collapse Inspired Robust Out-of-Distribution Detector0
Discriminability-Driven Channel Selection for Out-of-Distribution Detection0
Test-Time Linear Out-of-Distribution DetectionCode1
Towards Reliable AI Model Deployments: Multiple Input Mixup for Out-of-Distribution DetectionCode0
HyperMix: Out-of-Distribution Detection and Classification in Few-Shot Settings0
GROOD: Gradient-Aware Out-of-Distribution Detection0
Identity Curvature Laplace Approximation for Improved Out-of-Distribution DetectionCode0
Fast Decision Boundary based Out-of-Distribution DetectorCode0
Reliability in Semantic Segmentation: Can We Use Synthetic Data?Code1
EAT: Towards Long-Tailed Out-of-Distribution DetectionCode1
PAWS-VMK: A Unified Approach To Semi-Supervised Learning And Out-of-Distribution Detection0
Model-free Test Time Adaptation for Out-Of-Distribution Detection0
ID-like Prompt Learning for Few-Shot Out-of-Distribution DetectionCode1
RankFeat&RankWeight: Rank-1 Feature/Weight Removal for Out-of-distribution DetectionCode0
Towards Few-shot Out-of-Distribution Detection0
Deep Neural Network Identification of Limnonectes Species and New Class Detection Using Image Data0
Distilling the Unknown to Unveil CertaintyCode0
Topology-Matching Normalizing Flows for Out-of-Distribution Detection in Robot Learning0
Improvements on Uncertainty Quantification for Node Classification via Distance-Based RegularizationCode0
Out-of-distribution Detection Learning with Unreliable Out-of-distribution SourcesCode0
Detecting Out-of-Distribution Through the Lens of Neural CollapseCode0
Dual Conditioned Diffusion Models for Out-Of-Distribution Detection: Application to Fetal Ultrasound Videos0
Classifier-head Informed Feature Masking and Prototype-based Logit Smoothing for Out-of-Distribution Detection0
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