关键词：Anomaly Detection, Outlier Detection, Out-of-Distribution, Abnomal Detecting, Abnormal Detection, Defect DetectionInspection

A New Comprehensive Benchmark for Semi-Supervised Video Anomaly Detection and Anticipation

Block Selection Method for Using Feature Norm in Out-of-distribution Detection

Detection of out-of-distribution samples using binary neuron activation patterns

Decoupling MaxLogit for Out-of-Distribution Detection

Diversity-Measurable Anomaly Detection

DeSTSeg: Segmentation Guided Denoising Student-Teacher for Anomaly Detection

Explicit Boundary Guided Semi-Push-Pull Contrastive Learning for Supervised Anomaly Detection

GEN: Pushing the Limits of Softmax-Based Out-of-Distribution Detection

OmniAL: A unified CNN framework for unsupervised anomaly localization

Prototypical Residual Networks for Anomaly Detection and Localization

LINe: Out-of-Distribution Detection by Leveraging Important Neurons

Out-of-Distribution Detection by Leveraging Important Neurons

Multimodal Industrial Anomaly Detection via Hybrid Fusion

SimpleNet: A Simple Network for Image Anomaly Detection and Localization

Prompt-Guided Zero-Shot Anomaly Action Recognition using Pretrained Deep Skeleton Features

Self-Supervised Video Forensics by Audio-Visual Anomaly Detection

PyramidFlow: High-Resolution Defect Contrastive Localization using Pyramid Normalizing Flow

SQUID: Deep Feature In-Painting for Unsupervised Anomaly Detection

Look Around for Anomalies: Weakly-Supervised Anomaly Detection via Context-Motion Relational Learning

Uncertainty-Aware Optimal Transport for Semantically Coherent Out-of-Distribution Detection

Exploiting Completeness and Uncertainty of Pseudo Labels for Weakly Supervised Video Anomaly Detection

Revisiting Reverse Distillation for Anomaly Detection

Hierarchical Semantic Contrast for Scene-Aware Video Anomaly Detection

Video Event Restoration Based on Keyframes for Video Anomaly Detection

Generating Anomalies for Video Anomaly Detection With Prompt-Based Feature Mapping

Balanced Energy Regularization Loss for Out-of-distribution Detection

Multimodal Industrial Anomaly Detection via Hybrid Fusion

Prototypical Residual Networks for Anomaly Detection and Localization

Rethinking Out-of-distribution (OOD) Detection: Masked Image Modeling is All You Need

ICLR 2023

Unsupervised Model Selection for Time Series Anomaly Detection

Out-of-Distribution Detection and Selective Generation for Conditional Language Models

A framework for benchmarking Class-out-of-distribution detection and its application to ImageNet

Turning the Curse of Heterogeneity in Federated Learning into a Blessing for Out-of-Distribution Detection

AE-FLOW: Autoencoders with Normalizing Flows for Medical Images Anomaly Detection

RGI: robust GAN-inversion for mask-free image inpainting and unsupervised pixel-wise anomaly detection

Turning the Curse of Heterogeneity in Federated Learning into a Blessing for Out-of-Distribution Detection

Towards Lightweight, Model-Agnostic and Diversity-Aware Active Anomaly Detection

The Tilted Variational Autoencoder: Improving Out-of-Distribution Detection

Pushing the Limits of Fewshot Anomaly Detection in Industry Vision: Graphcore

How to Exploit Hyperspherical Embeddings for Out-of-Distribution Detection?

Extremely Simple Activation Shaping for Out-of-Distribution Detection

Red PANDA: Disambiguating Image Anomaly Detection by Removing Nuisance Factors

Out-of-distribution Detection with Implicit Outlier Transformation

Energy-based Out-of-Distribution Detection for Graph Neural Networks

mbd.pub/o/GeBENHAGEN

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