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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/hazardfy/fiba

공식 코드

FIBA: Frequency-Injection based Backdoor Attack in Medical Image Analysis

https://github.com/hbhzwj/SADIT

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Statistical Anomaly Detection via Composite Hypothesis Testing for Markov Models

https://github.com/hc-guo/logformer

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LogFormer: A Pre-train and Tuning Pipeline for Log Anomaly Detection

https://github.com/hellodfan/ai4graininsp

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Identifying the Defective: Detecting Damaged Grains for Cereal Appearance Inspection

https://github.com/hendrycks/error-detection

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A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

https://github.com/hendrycks/outlier-exposure

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Deep Anomaly Detection with Outlier Exposure

https://github.com/hendrycks/ss-ood

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Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty

https://github.com/henrryzh1/MA-PDM

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Video Anomaly Detection with Motion and Appearance Guided Patch Diffusion Model

https://github.com/henrryzh1/UR-DMU

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Dual Memory Units with Uncertainty Regulation for Weakly Supervised Video Anomaly Detection

https://github.com/hep-lbdl/gaiacwola

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Weakly-Supervised Anomaly Detection in the Milky Way

https://github.com/hep-lbdl/paws-sbi

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Generator Based Inference (GBI)

https://github.com/hepta-col/videofightdetection

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Weakly Supervised Two-Stage Training Scheme for Deep Video Fight Detection Model

https://github.com/hermannsblum/fishyscapes

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The Fishyscapes Benchmark: Measuring Blind Spots in Semantic Segmentation

https://github.com/heyonghu/tiny-ppg

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Tiny-PPG: A Lightweight Deep Neural Network for Real-Time Detection of Motion Artifacts in Photoplethysmogram Signals on Edge Devices

https://github.com/hibrahimozturk/temporal_anomaly_detection

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ADNet: Temporal Anomaly Detection in Surveillance Videos

https://github.com/hito2448/CRD

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Multimodal Industrial Anomaly Detection by Crossmodal Reverse Distillation

https://github.com/hito2448/urd

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Unlocking the Potential of Reverse Distillation for Anomaly Detection

https://github.com/hkuedl/Task-Oriented-Imputation

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Task-oriented Time Series Imputation Evaluation via Generalized Representers

https://github.com/hlr7999/rlr

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Learning Unified Reference Representation for Unsupervised Multi-class Anomaly Detection

https://github.com/hlwang1124/GMRPD

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Dynamic Fusion Module Evolves Drivable Area and Road Anomaly Detection: A Benchmark and Algorithms

https://github.com/hlwang1124/NIM

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Applying Surface Normal Information in Drivable Area and Road Anomaly Detection for Ground Mobile Robots

https://github.com/hmsch/natural-synthetic-anomalies

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Natural Synthetic Anomalies for Self-Supervised Anomaly Detection and Localization

https://github.com/hongh0/iqe-clip

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IQE-CLIP: Instance-aware Query Embedding for Zero-/Few-shot Anomaly Detection in Medical Domain

https://github.com/houssamzenati/Adversarially-Learned-Anomaly-Detection

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Adversarially Learned Anomaly Detection

https://github.com/houssamzenati/Efficient-GAN-Anomaly-Detection

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Efficient GAN-Based Anomaly Detection

https://github.com/hq-deng/AnoVL

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Bootstrap Fine-Grained Vision-Language Alignment for Unified Zero-Shot Anomaly Localization

https://github.com/hq-deng/RD4AD

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Anomaly Detection via Reverse Distillation from One-Class Embedding

https://github.com/hsipingli/chigad

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Chi-Square Wavelet Graph Neural Networks for Heterogeneous Graph Anomaly Detection

https://github.com/huankoh/cst-gl

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Correlation-aware Spatial-Temporal Graph Learning for Multivariate Time-series Anomaly Detection

https://github.com/huaweicloud/c2far_forecasting

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C2FAR: Coarse-to-Fine Autoregressive Networks for Precise Probabilistic Forecasting

https://github.com/huchao-ai/apn

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Normal Learning in Videos with Attention Prototype Network

https://github.com/hugothimonier/TracInAD

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TracInAD: Measuring Influence for Anomaly Detection

https://github.com/hugothimonier/making-parametric-anomaly-detection-on-tabular-data-non-parametric-again

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Retrieval Augmented Deep Anomaly Detection for Tabular Data

https://github.com/hugothimonier/npt-ad

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Beyond Individual Input for Deep Anomaly Detection on Tabular Data

https://github.com/hugothimonier/retrieval-augmented-deep-anomaly-detection-for-tabular-data

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Retrieval Augmented Deep Anomaly Detection for Tabular Data

https://github.com/hui-design/aand

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Advancing Pre-trained Teacher: Towards Robust Feature Discrepancy for Anomaly Detection

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.