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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/huizhang0812/diffusionad

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DiffusionAD: Norm-guided One-step Denoising Diffusion for Anomaly Detection

https://github.com/hulei7/replaycad

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ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection

https://github.com/hust-slow/anomalyncd

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AnomalyNCD: Towards Novel Anomaly Class Discovery in Industrial Scenarios

https://github.com/hustCYQ/GLFM-Multi-class-3DAD

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Boosting Global-Local Feature Matching via Anomaly Synthesis for Multi-Class Point Cloud Anomaly Detection

https://github.com/hustCYQ/MiniShift-Simple3D

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Towards High-Resolution 3D Anomaly Detection: A Scalable Dataset and Real-Time Framework for Subtle Industrial Defects

https://github.com/hustCYQ/RAD-dataset

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RAD: A Comprehensive Dataset for Benchmarking the Robustness of Image Anomaly Detection

https://github.com/hustcyq/mvp-pclip

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Towards Zero-shot Point Cloud Anomaly Detection: A Multi-View Projection Framework

https://github.com/huyhieupham/learning-from-multiple-annotators

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Learning from Multiple Expert Annotators for Enhancing Anomaly Detection in Medical Image Analysis

https://github.com/huzongxiang/sowa

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SOWA: Adapting Hierarchical Frozen Window Self-Attention to Visual-Language Models for Better Anomaly Detection

https://github.com/hy-vision-lab/funad

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FUN-AD: Fully Unsupervised Learning for Anomaly Detection with Noisy Training Data

https://github.com/hyao1/glad

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GLAD: Towards Better Reconstruction with Global and Local Adaptive Diffusion Models for Unsupervised Anomaly Detection

https://github.com/hzlsaber/IPMix

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IPMix: Label-Preserving Data Augmentation Method for Training Robust Classifiers

https://github.com/hzzzzzhappy/mc4ad

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Examining the Source of Defects from a Mechanical Perspective for 3D Anomaly Detection

https://github.com/iamcuriosity/wscxr

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Weakly Supervised Anomaly Detection for Chest X-Ray Image

https://github.com/ibrahimethemhamamci/ct-clip

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Developing Generalist Foundation Models from a Multimodal Dataset for 3D Computed Tomography

https://github.com/icsdataset/hai

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MAD: Self-Supervised Masked Anomaly Detection Task for Multivariate Time Series

https://github.com/idsia-robotics/hazard-detection

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Sensing Anomalies as Potential Hazards: Datasets and Benchmarks

https://github.com/idt-iti/mmfusion-iml

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MMFusion: Combining Image Forensic Filters for Visual Manipulation Detection and Localization

https://github.com/igcondapet/igconda-pet

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IgCONDA-PET: Weakly-Supervised PET Anomaly Detection using Implicitly-Guided Attention-Conditional Counterfactual Diffusion Modeling -- a Multi-Center, Multi-Cancer, and Multi-Tracer Study

https://github.com/ilkyyldz95/eeg_mvts

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Unsupervised Multivariate Time-Series Transformers for Seizure Identification on EEG

https://github.com/ilyakava/pyfst

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Three-Dimensional Fourier Scattering Transform and Classification of Hyperspectral Images

https://github.com/ilyakava/tfST

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Three-Dimensional Fourier Scattering Transform and Classification of Hyperspectral Images

https://github.com/ilyesbenaissa/MAAT

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MAAT: Mamba Adaptive Anomaly Transformer with association discrepancy for time series

https://github.com/imics-lab/positional-encoding-benchmark

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Positional Encoding in Transformer-Based Time Series Models: A Survey

https://github.com/imperial-qore/gon

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Generative Optimization Networks for Memory Efficient Data Generation

https://github.com/imperial-qore/gon_mnist

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Generative Optimization Networks for Memory Efficient Data Generation

https://github.com/imperial-qore/tranad

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TranAD: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series Data

https://github.com/implabunipr/movad

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Memory-augmented Online Video Anomaly Detection

https://github.com/imrl/umad

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UMAD: University of Macau Anomaly Detection Benchmark Dataset

https://github.com/ineveloppilif/hashing-for-structure-based-anomaly-detection

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Hashing for Structure-based Anomaly Detection

https://github.com/ineveloppilif/online-isolation-forest

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Online Isolation Forest

https://github.com/inkiinki/mi-uap

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Interpreting Vulnerabilities of Multi-Instance Learning to Adversarial Perturbations

https://github.com/inspire-group/SSD

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SSD: A Unified Framework for Self-Supervised Outlier Detection

https://github.com/institute-eng-and-comp-mechanics-ustgt/antagonisticagents

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Discovering Antagonists in Networks of Systems: Robot Deployment

https://github.com/intelligolabs/kairosad

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KairosAD: A SAM-Based Model for Industrial Anomaly Detection on Embedded Devices

https://github.com/intrudetection/robevalanodetect

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Robustness Evaluation of Deep Unsupervised Learning Algorithms for Intrusion Detection Systems

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