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One-Class Classification

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.

Papers

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Showing 1–50 of 227 papers

TitleStatusHype
FUN-AD: Fully Unsupervised Learning for Anomaly Detection with Noisy Training DataCode1
Which Model Generated This Image? A Model-Agnostic Approach for Origin AttributionCode1
PREGO: online mistake detection in PRocedural EGOcentric videosCode1
Interleaving One-Class and Weakly-Supervised Models with Adaptive Thresholding for Unsupervised Video Anomaly DetectionCode1
Label-Free Multivariate Time Series Anomaly DetectionCode1
A Coarse-to-Fine Pseudo-Labeling (C2FPL) Framework for Unsupervised Video Anomaly DetectionCode1
Multimodal Motion Conditioned Diffusion Model for Skeleton-based Video Anomaly DetectionCode1
Diversity-Measurable Anomaly DetectionCode1
Anomaly Segmentation for High-Resolution Remote Sensing Images Based on Pixel DescriptorsCode1
Inter-Realization Channels: Unsupervised Anomaly Detection Beyond One-Class ClassificationCode1
DeSTSeg: Segmentation Guided Denoising Student-Teacher for Anomaly DetectionCode1
One-Class Risk Estimation for One-Class Hyperspectral Image ClassificationCode1
Self-Supervised Masked Convolutional Transformer Block for Anomaly DetectionCode1
Calibrated One-class Classification for Unsupervised Time Series Anomaly DetectionCode1
Deep Contrastive One-Class Time Series Anomaly DetectionCode1
Dual-Distribution Discrepancy for Anomaly Detection in Chest X-RaysCode1
Anomaly Detection in Emails using Machine Learning and Header InformationCode1
Self-Supervised Predictive Convolutional Attentive Block for Anomaly DetectionCode1
UBnormal: New Benchmark for Supervised Open-Set Video Anomaly DetectionCode1
Learning Not to Reconstruct AnomaliesCode1
Synthetic Temporal Anomaly Guided End-to-End Video Anomaly DetectionCode1
Deep One-Class Classification via Interpolated Gaussian DescriptorCode1
MOCCA: Multi-Layer One-Class ClassificAtion for Anomaly DetectionCode1
Learning and Evaluating Representations for Deep One-class ClassificationCode1
PANDA: Adapting Pretrained Features for Anomaly Detection and SegmentationCode1
Meta Learning for Few-Shot One-class ClassificationCode1
Few-Shot One-Class Classification via Meta-LearningCode1
Explainable Deep One-Class ClassificationCode1
Viral Pneumonia Screening on Chest X-ray Images Using Confidence-Aware Anomaly DetectionCode1
One-Class Graph Neural Networks for Anomaly Detection in Attributed NetworksCode1
Unsupervised Traffic Accident Detection in First-Person VideosCode1
One-Class Convolutional Neural NetworkCode1
SD-MAD: Sign-Driven Few-shot Multi-Anomaly Detection in Medical Images—0
Adversarial Subspace Generation for Outlier Detection in High-Dimensional DataCode0
RoCA: Robust Contrastive One-class Time Series Anomaly Detection with Contaminated DataCode0
From Pixels to Trajectory: Universal Adversarial Example Detection via Temporal Imprints—0
FedDyMem: Efficient Federated Learning with Dynamic Memory and Memory-Reduce for Unsupervised Image Anomaly Detection—0
Anomaly Detection in Smart Power Grids with Graph-Regularized MS-SVDD: a Multimodal Subspace Learning Approach—0
One Class Restricted Kernel MachinesCode0
Teacher Encoder-Student Decoder Denoising Guided Segmentation Network for Anomaly Detection—0
Score Combining for Contrastive OOD Detection—0
On the Adversarial Robustness of Benjamini Hochberg—0
Beyond Generation: A Diffusion-based Low-level Feature Extractor for Detecting AI-generated Images—0
Task-Specific Gradient Adaptation for Few-Shot One-Class Classification—0
MEATRD: Multimodal Anomalous Tissue Region Detection Enhanced with Spatial TranscriptomicsCode0
Disentangling Tabular Data Towards Better One-Class Anomaly DetectionCode0
Point Cloud Novelty Detection Based on Latent Representations of a General Feature Extractor—0
On The Relationship between Visual Anomaly-free and Anomalous Representations—0
Linear-time One-Class Classification with Repeated Element-wise FoldingCode0
Non-Robust Features are Not Always Useful in One-Class Classification—0
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