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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/yali-f/gladmamba

공식 코드

GLADMamba: Unsupervised Graph-Level Anomaly Detection Powered by Selective State Space Model

https://github.com/yali-f/hc-glad

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HC-GLAD: Dual Hyperbolic Contrastive Learning for Unsupervised Graph-Level Anomaly Detection

https://github.com/yan123yan/hdr-anomaly-challenge-submission

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DeepGrav: Anomalous Gravitational-Wave Detection Through Deep Latent Features

https://github.com/yanir75/gnn-anomalydetection

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Cloudy with a Chance of Anomalies: Dynamic Graph Neural Network for Early Detection of Cloud Services' User Anomalies

https://github.com/yashasvi97/IJCB2020_anomaly

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Anomaly Detection-Based Unknown Face Presentation Attack Detection

https://github.com/yc-cui/super-ad

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Overcoming the Identity Mapping Problem in Self-Supervised Hyperspectral Anomaly Detection

https://github.com/ydup/Anomaly-Detection-in-Time-Series-with-Triadic-Motif-Fields

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Anomaly Detection in Time Series with Triadic Motif Fields and Application in Atrial Fibrillation ECG Classification

https://github.com/ydup/bokeh

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Anomaly Detection in Time Series with Triadic Motif Fields and Application in Atrial Fibrillation ECG Classification

https://github.com/yedidh/radonomaly

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Time Series Anomaly Detection by Cumulative Radon Features

https://github.com/yhZhai/WSCL

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Towards Generic Image Manipulation Detection with Weakly-Supervised Self-Consistency Learning

https://github.com/yhbcode000/MMDetection3D-Eloss

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Eloss in the way: A Sensitive Input Quality Metrics for Intelligent Driving

https://github.com/yifeilin0226/fastlogad

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FastLogAD: Log Anomaly Detection with Mask-Guided Pseudo Anomaly Generation and Discrimination

https://github.com/yihaoang/tsgbench

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TSGBench: Time Series Generation Benchmark

https://github.com/yinyjin/dualanodiff

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DualAnoDiff: Dual-Interrelated Diffusion Model for Few-Shot Anomaly Image Generation

https://github.com/yiweilu3/Few-shot-Scene-adaptive-Anomaly-Detection

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Few-shot Scene-adaptive Anomaly Detection

https://github.com/yixinliu233/arc

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ARC: A Generalist Graph Anomaly Detector with In-Context Learning

https://github.com/yixinliu233/signet

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Towards Self-Interpretable Graph-Level Anomaly Detection

https://github.com/yjnanan/disent-ad

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Disentangling Tabular Data Towards Better One-Class Anomaly Detection

https://github.com/yl-shen/dcad-2000

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DCAD-2000: A Multilingual Dataset across 2000+ Languages with Data Cleaning as Anomaly Detection

https://github.com/ymirsky/CIoTA-Sim

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Lightweight Collaborative Anomaly Detection for the IoT using Blockchain

https://github.com/yoavarad/mfad

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Beyond the Benchmark: Detecting Diverse Anomalies in Videos

https://github.com/yonatansverdlov/irreducible-representations-of-deep-weight-spaces

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Revisiting Multi-Permutation Equivariance through the Lens of Irreducible Representations

https://github.com/yoojlee/uniformaly

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UniFormaly: Towards Task-Agnostic Unified Framework for Visual Anomaly Detection

https://github.com/yoshall/awesome-trajectory-computing

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Deep Learning for Trajectory Data Management and Mining: A Survey and Beyond

https://github.com/youpengl/FedCAP

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FedCAP: Robust Federated Learning via Customized Aggregation and Personalization

https://github.com/yuan-12138/synomaly

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Synomaly Noise and Multi-Stage Diffusion: A Novel Approach for Unsupervised Anomaly Detection in Ultrasound Imaging

https://github.com/yuandou168/price

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PriCE: Privacy-Preserving and Cost-Effective Scheduling for Parallelizing the Large Medical Image Processing Workflow over Hybrid Clouds

https://github.com/yuanpengtu/sleeg

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Self-Supervised Likelihood Estimation with Energy Guidance for Anomaly Segmentation in Urban Scenes

https://github.com/yuedumingz/PointCore

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PointCore: Efficient Unsupervised Point Cloud Anomaly Detector Using Local-Global Features

https://github.com/yuehu9/Con-GAE

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Graph Convolutional Networks for traffic anomaly

https://github.com/yuehu9/dsab-detecting-socially-abnormal-drving-behaviors

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Detecting Socially Abnormal Highway Driving Behaviors via Recurrent Graph Attention Networks

https://github.com/yuguangnudt/VEC_VAD

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Cloze Test Helps: Effective Video Anomaly Detection via Learning to Complete Video Events

https://github.com/yuhbai/DFD

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Dual-path Frequency Discriminators for Few-shot Anomaly Detection

https://github.com/yujiangpu20/pel4vad

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Learning Prompt-Enhanced Context Features for Weakly-Supervised Video Anomaly Detection

https://github.com/yujinhan98/csforest

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Conformalized Semi-supervised Random Forest for Classification and Abnormality Detection

https://github.com/yul-git/glocalclip

공식 코드

GlocalCLIP: Object-agnostic Global-Local Prompt Learning for Zero-shot Anomaly Detection

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