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Anomaly Detection

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하위 태스크: 28
평가표: 76
보존된 평가 기록: 669

Anomaly Detection is a binary classification identifying unusual or unexpected patterns in a dataset, which deviate significantly from the majority of the data. The goal of anomaly detection is to identify such anomalies, which could represent errors, fraud, or other types of unusual events, and flag them for further investigation.

[Image source]: GAN-based Anomaly Detection in Imbalance Problems

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/xaggi/OGNet

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Old is Gold: Redefining the Adversarially Learned One-Class Classifier Training Paradigm

https://github.com/xcyao00/bgad

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

https://github.com/xcyao00/fod

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Focus the Discrepancy: Intra- and Inter-Correlation Learning for Image Anomaly Detection

https://github.com/xcyao00/hgad

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Hierarchical Gaussian Mixture Normalizing Flow Modeling for Unified Anomaly Detection

https://github.com/xcyao00/resad

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ResAD: A Simple Framework for Class Generalizable Anomaly Detection

https://github.com/xgu1/DTM

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Statistical Analysis of Nearest Neighbor Methods for Anomaly Detection

https://github.com/xiagll/optiforest

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OptIForest: Optimal Isolation Forest for Anomaly Detection

https://github.com/xiao-he/oneshotstl

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OneShotSTL: One-Shot Seasonal-Trend Decomposition For Online Time Series Anomaly Detection And Forecasting

https://github.com/xiaofeng-tan/fgdmad-code

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Frequency-Guided Diffusion Model with Perturbation Training for Skeleton-Based Video Anomaly Detection

https://github.com/xiaogangpeng/hypervd

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Learning Weakly Supervised Audio-Visual Violence Detection in Hyperbolic Space

https://github.com/xiaohao-xu/customizable-vlm

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Customizing Visual-Language Foundation Models for Multi-modal Anomaly Detection and Reasoning

https://github.com/xiaoyuanguo/tend_medicalnoveltydetection

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Margin-Aware Intra-Class Novelty Identification for Medical Images

https://github.com/xiaozhen228/Bayes-PFL

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Bayesian Prompt Flow Learning for Zero-Shot Anomaly Detection

https://github.com/xiaozhen228/vcp-clip

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VCP-CLIP: A visual context prompting model for zero-shot anomaly segmentation

https://github.com/xiat0616/pseudo-healthy-synthesis

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Pseudo-healthy synthesis with pathology disentanglement and adversarial learning

https://github.com/ximenafernandez/intrinsicPH

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Intrinsic persistent homology via density-based metric learning

https://github.com/xinlihao/aero

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From Chaos to Clarity: Time Series Anomaly Detection in Astronomical Observations

https://github.com/xinyi-0724/smarthome-bench-llm

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SmartHome-Bench: A Comprehensive Benchmark for Video Anomaly Detection in Smart Homes Using Multi-Modal Large Language Models

https://github.com/xiongxiaoxu/metagad

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MetaGAD: Meta Representation Adaptation for Few-Shot Graph Anomaly Detection

https://github.com/xjiae/arpro

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AR-Pro: Counterfactual Explanations for Anomaly Repair with Formal Properties

https://github.com/xjpp2016/mavd

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Aligning First, Then Fusing: A Novel Weakly Supervised Multimodal Violence Detection Method

https://github.com/xjspin/ISSTAD

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ISSTAD: Incremental Self-Supervised Learning Based on Transformer for Anomaly Detection and Localization

https://github.com/xjywhu/smartguard

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Make Your Home Safe: Time-aware Unsupervised User Behavior Anomaly Detection in Smart Homes via Loss-guided Mask

https://github.com/xrli-U/MuSc

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MuSc: Zero-Shot Industrial Anomaly Classification and Segmentation with Mutual Scoring of the Unlabeled Images

https://github.com/xrli-u/robis

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RoBiS: Robust Binary Segmentation for High-Resolution Industrial Images

https://github.com/xuhongzuo/DeepOD

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Fascinating Supervisory Signals and Where to Find Them: Deep Anomaly Detection with Scale Learning

https://github.com/xuhongzuo/couta

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Calibrated One-class Classification for Unsupervised Time Series Anomaly Detection

https://github.com/xuhongzuo/deep-iforest

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Deep Isolation Forest for Anomaly Detection

https://github.com/xuhongzuo/rosas

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RoSAS: Deep Semi-Supervised Anomaly Detection with Contamination-Resilient Continuous Supervision

https://github.com/xuhongzuo/scale-learning

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Fascinating Supervisory Signals and Where to Find Them: Deep Anomaly Detection with Scale Learning

https://github.com/xuqinghua-china/tosem

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Digital Twin-based Anomaly Detection with Curriculum Learning in Cyber-physical Systems

https://github.com/xxhu94/gat-cobo

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GAT-COBO: Cost-Sensitive Graph Neural Network for Telecom Fraud Detection

https://github.com/xycheng/EmbeddingNorm

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Spectral Embedding Norm: Looking Deep into the Spectrum of the Graph Laplacian

https://github.com/xydong127/rqgnn

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Rayleigh Quotient Graph Neural Networks for Graph-level Anomaly Detection

https://github.com/xydong127/spacegnn

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SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited Labels

https://github.com/ya0-sun/posteq-saropt-buildingdamage

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QuickQuakeBuildings: Post-earthquake SAR-Optical Dataset for Quick Damaged-building Detection

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