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One-Class Classification

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One-class classification (OCC) algorithms serve a crucial role in scenarios where the negative class is either absent, poorly sampled, or not well defined. This unique situation presents a challenge for building effective classifiers, as they must delineate the class boundary solely based on knowledge of the positive class. OCC has found application in various research domains, including outlier/novelty detection and concept learning.

In the context of anomaly detection, OCC models are trained exclusively on "normal" data and are subsequently tasked with identifying anomalous patterns during inference.

A one-class classifier aims at capturing characteristics of training instances, in order to be able to distinguish between them and potential outliers to appear.

— Page 139, Learning from Imbalanced Data Sets, 2018.

논문

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One-Class Classification

논문

FedDyMem: Efficient Federated Learning with Dynamic Memory and Memory-Reduce for Unsupervised Image Anomaly Detection

SD-MAD: Sign-Driven Few-shot Multi-Anomaly Detection in Medical Images

Adversarial Subspace Generation for Outlier Detection in High-Dimensional Data

RoCA: Robust Contrastive One-class Time Series Anomaly Detection with Contaminated Data

From Pixels to Trajectory: Universal Adversarial Example Detection via Temporal Imprints

Anomaly Detection in Smart Power Grids with Graph-Regularized MS-SVDD: a Multimodal Subspace Learning Approach

One Class Restricted Kernel Machines

Teacher Encoder-Student Decoder Denoising Guided Segmentation Network for Anomaly Detection

Score Combining for Contrastive OOD Detection

On the Adversarial Robustness of Benjamini Hochberg

MEATRD: Multimodal Anomalous Tissue Region Detection Enhanced with Spatial Transcriptomics

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

Disentangling Tabular Data Towards Better One-Class Anomaly Detection

Point Cloud Novelty Detection Based on Latent Representations of a General Feature Extractor

On The Relationship between Visual Anomaly-free and Anomalous Representations

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

Non-Robust Features are Not Always Useful in One-Class Classification

Quality assurance of organs-at-risk delineation in radiotherapy

One-Class Classification as GLRT for Jamming Detection in Private 5G Networks

Critical Review for One-class Classification: recent advances and the reality behind them

Hyp-OC: Hyperbolic One Class Classification for Face Anti-Spoofing

Which Model Generated This Image? A Model-Agnostic Approach for Origin Attribution

PREGO: online mistake detection in PRocedural EGOcentric videos

LLM meets Vision-Language Models for Zero-Shot One-Class Classification

usfAD Based Effective Unknown Attack Detection Focused IDS Framework

A Dual-Tier Adaptive One-Class Classification IDS for Emerging Cyberthreats

Refining Myocardial Infarction Detection: A Novel Multi-Modal Composite Kernel Strategy in One-Class Classification

Understanding Time Series Anomaly State Detection through One-Class Classification

Trustworthiness of $\mathbb{X}$ Users: A One-Class Classification Approach

Interleaving One-Class and Weakly-Supervised Models with Adaptive Thresholding for Unsupervised Video Anomaly Detection

Lp-Norm Constrained One-Class Classifier Combination

Advancing Image Retrieval with Few-Shot Learning and Relevance Feedback

Label-Free Multivariate Time Series Anomaly Detection

Learning Polynomial Representations of Physical Objects with Application to Certifying Correct Packing Configurations

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

Video Anomaly Detection via Spatio-Temporal Pseudo-Anomaly Generation : A Unified Approach