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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/iolag/upd_study

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Unsupervised Pathology Detection: A Deep Dive Into the State of the Art

https://github.com/ireydiak/anomaly_detection_nrcan

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A Revealing Large-Scale Evaluation of Unsupervised Anomaly Detection Algorithms

https://github.com/ironing/eeg-ad

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Task-oriented Self-supervised Learning for Anomaly Detection in Electroencephalography

https://github.com/irxyzzz/DualDefense

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Dual Defense: Enhancing Privacy and Mitigating Poisoning Attacks in Federated Learning

https://github.com/isla-lab/causal_anomaly_detection

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Explainable Online Unsupervised Anomaly Detection for Cyber-Physical Systems via Causal Discovery from Time Series

https://github.com/isotlaboratory/UNAVOIDS-Code

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UN-AVOIDS: Unsupervised and Nonparametric Approach for Visualizing Outliers and Invariant Detection Scoring

https://github.com/issaccv/KAN-AD

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KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks

https://github.com/iulianhiji/ad-dl-ocsvm

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Fusing Dictionary Learning and Support Vector Machines for Unsupervised Anomaly Detection

https://github.com/ividja/Probabilistic-PII

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Confidence-Aware and Self-Supervised Image Anomaly Localisation

https://github.com/ivineetm007/Fall-detection

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Motion and Region Aware Adversarial Learning for Fall Detection with Thermal Imaging

https://github.com/izikgo/AnomalyDetectionTransformations

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Deep Anomaly Detection Using Geometric Transformations

https://github.com/j4sabuda/braced-fourier-continuation-and-regression

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Braced Fourier Continuation and Regression for Anomaly Detection

https://github.com/jLooo/VADMamba

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VADMamba: Exploring State Space Models for Fast Video Anomaly Detection

https://github.com/jackaraz/qvae-anomaly

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The role of data embedding in quantum autoencoders for improved anomaly detection

https://github.com/jackyue1994/sub_adjacent_transformer

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Sub-Adjacent Transformer: Improving Time Series Anomaly Detection with Reconstruction Error from Sub-Adjacent Neighborhoods

https://github.com/jaeminyoo/dsv

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DSV: An Alignment Validation Loss for Self-supervised Outlier Model Selection

https://github.com/jaeminyoo/ssl-ad

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Data Augmentation is a Hyperparameter: Cherry-picked Self-Supervision for Unsupervised Anomaly Detection is Creating the Illusion of Success

https://github.com/jakubmicorek/MULDE-Multiscale-Log-Density-Estimation-via-Denoising-Score-Matching-for-Video-Anomaly-Detection

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MULDE: Multiscale Log-Density Estimation via Denoising Score Matching for Video Anomaly Detection

https://github.com/jam-cc/mmad

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MMAD: The First-Ever Comprehensive Benchmark for Multimodal Large Language Models in Industrial Anomaly Detection

https://github.com/jameszhou-gl/gpt-4v-distribution-shift

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How Well Does GPT-4V(ision) Adapt to Distribution Shifts? A Preliminary Investigation

https://github.com/jarartur/histopathologyaugmentationresearch

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Improving Quality Control of Whole Slide Images by Explicit Artifact Augmentation

https://github.com/jayaram-r/adversarial-detection

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A General Framework For Detecting Anomalous Inputs to DNN Classifiers

https://github.com/jbr-ai-labs/pu-oc

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Improving State-of-the-Art in One-Class Classification by Leveraging Unlabeled Data

https://github.com/jcribeiro98/v-gan

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Adversarial Subspace Generation for Outlier Detection in High-Dimensional Data

https://github.com/jemtan/PII

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Detecting Outliers with Poisson Image Interpolation

https://github.com/jenniraitoharju/generalizedreferencekernel

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Generalized Reference Kernel for One-class Classification

https://github.com/jenniraitoharju/ref

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Linear-time One-Class Classification with Repeated Element-wise Folding

https://github.com/jhkim611/clad

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Class Label-aware Graph Anomaly Detection

https://github.com/jhornauer/mde_ood

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Out-of-Distribution Detection for Monocular Depth Estimation

https://github.com/jhryu30/anomalybert

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AnomalyBERT: Self-Supervised Transformer for Time Series Anomaly Detection using Data Degradation Scheme

https://github.com/jhsk777/slade

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SLADE: Detecting Dynamic Anomalies in Edge Streams without Labels via Self-Supervised Learning

https://github.com/jhsk777/slade-online-appendix

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SLADE: Detecting Dynamic Anomalies in Edge Streams without Labels via Self-Supervised Learning

https://github.com/jhy549/ocgec

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OCGEC: One-class Graph Embedding Classification for DNN Backdoor Detection

https://github.com/jianganbai/aegan-ad

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Unsupervised Anomaly Detection and Localization of Machine Audio: A GAN-based Approach

https://github.com/jianzhang96/goodsad

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PKU-GoodsAD: A Supermarket Goods Dataset for Unsupervised Anomaly Detection and Segmentation

https://github.com/jiaxililearn/hrgcn

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HRGCN: Heterogeneous Graph-level Anomaly Detection with Hierarchical Relation-augmented Graph Neural Networks

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