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
擅长现代信号处理(改进小波分析系列，改进变分模态分解，改进经验小波变换，改进辛几何模态分解等等)，改进机器学习，改进深度学习，机械故障诊断，改进时间序列分析(金融信号，心电信号，振动信号等)
