Supervised Anomaly Detection

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

2 leaderboard tables shown for this task, 2 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

4 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 67 papers with code (155 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training
  17 May 2018 8 repositories listed Syntology ran 0 of 23 samples · 23 unverified
  Anomaly detection is a classical problem in computer vision, namely the determination of the normal from the abnormal when datasets are highly biased towards one class (normal) due to the insufficient sample size of the…
• Deep Semi-Supervised Anomaly Detection
  6 Jun 2019 7 repositories listed Syntology ran 0 of 2 samples · 2 unverified
  Deep approaches to anomaly detection have recently shown promising results over shallow methods on large and complex datasets.
• Deep Weakly-supervised Anomaly Detection
  30 Oct 2019 4 repositories listed Syntology ran 5 of 6 samples · 1 unverified
  To detect both seen and unseen anomalies, we introduce a novel deep weakly-supervised approach, namely Pairwise Relation prediction Network (PReNet), that learns pairwise relation features and anomaly scores by…
• Natural Synthetic Anomalies for Self-Supervised Anomaly Detection and Localization
  30 Sep 2021 3 repositories listed Syntology ran 2 of 8 samples · 6 unverified
  We introduce a simple and intuitive self-supervision task, Natural Synthetic Anomalies (NSA), for training an end-to-end model for anomaly detection and localization using only normal training data.
• Supervised Anomaly Detection for Complex Industrial Images
  8 May 2024 2 repositories listed
  Acknowledging that traditional AD methods struggle with this dataset, we introduce (2) Segmentation-based Anomaly Detector (SegAD).
• IgCONDA-PET: Weakly-Supervised PET Anomaly Detection using Implicitly-Guided Attention-Conditional Counterfactual Diffusion Modeling -- a Multi-Center, Multi-Cancer, and Multi-Tracer Study
  30 Apr 2024 2 repositories listed
  The training is conditioned on image class labels (healthy vs.
• Weakly-Supervised Video Anomaly Detection with Snippet Anomalous Attention
  28 Sep 2023 2 repositories listed
  Our approach takes into account snippet-level encoded features without the supervision of pseudo labels.
• Label-based Graph Augmentation with Metapath for Graph Anomaly Detection
  21 Aug 2023 2 repositories listed Syntology ran 3 of 4 samples · 1 unverified · 4 pointer-only (licence)
  To further efficiently exploit context information from metapath-based anomaly subgraph, we present a new framework, Metapath-based Graph Anomaly Detection (MGAD), incorporating GCN layers in both the dual-encoders and…
• ImbSAM: A Closer Look at Sharpness-Aware Minimization in Class-Imbalanced Recognition
  15 Aug 2023 2 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  To overcome this bottleneck, we leverage class priors to restrict the generalization scope of the class-agnostic SAM and propose a class-aware smoothness optimization algorithm named Imbalanced-SAM (ImbSAM).
• Weakly Supervised Anomaly Detection: A Survey
  9 Feb 2023 2 repositories listed Syntology ran 1 of 3 samples · 2 unverified
  Anomaly detection (AD) is a crucial task in machine learning with various applications, such as detecting emerging diseases, identifying financial frauds, and detecting fake news.
• Leveraging Contaminated Datasets to Learn Clean-Data Distribution with Purified Generative Adversarial Networks
  3 Feb 2023 2 repositories listed
  When training on such datasets, existing GANs will learn a mixture distribution of desired and contaminated instances, rather than the desired distribution of desired data only (target distribution).
• Diffusion Models for Medical Anomaly Detection
  8 Mar 2022 2 repositories listed Syntology ran 11 of 23 samples · 12 unverified · 2 pointer-only (licence)
  In medical applications, weakly supervised anomaly detection methods are of great interest, as only image-level annotations are required for training.
• Feature Encoding with AutoEncoders for Weakly-supervised Anomaly Detection
  22 May 2021 2 repositories listed
  Weakly-supervised anomaly detection aims at learning an anomaly detector from a limited amount of labeled data and abundant unlabeled data.
• Supervised Anomaly Detection via Conditional Generative Adversarial Network and Ensemble Active Learning
  24 Apr 2021 2 repositories listed
  In addition to using the conditional GAN to generate class balanced supplementary training data, an innovative ensemble learning loss function ensuring each discriminator makes up for the deficiencies of the others is…
• Toward Deep Supervised Anomaly Detection: Reinforcement Learning from Partially Labeled Anomaly Data
  15 Sep 2020 2 repositories listed Syntology ran 0 of 6 samples · 6 unverified
  We consider the problem of anomaly detection with a small set of partially labeled anomaly examples and a large-scale unlabeled dataset.
• How to Evaluate the Quality of Unsupervised Anomaly Detection Algorithms?
  5 Jul 2016 2 repositories listed Syntology ran 1 of 2 samples · 1 unverified
  When sufficient labeled data are available, classical criteria based on Receiver Operating Characteristic (ROC) or Precision-Recall (PR) curves can be used to compare the performance of un-supervised anomaly detection…
• Few-Shot Anomaly-Driven Generation for Anomaly Classification and Segmentation
  14 May 2025 1 repository listed
  The experiments demonstrate that our generated anomalies effectively improve the model performance of both anomaly classification and segmentation tasks simultaneously, \eg, DRAEM and DseTSeg achieved a 5.
• ProDisc-VAD: An Efficient System for Weakly-Supervised Anomaly Detection in Video Surveillance Applications
  4 May 2025 1 repository listed
  Weakly-supervised video anomaly detection (WS-VAD) using Multiple Instance Learning (MIL) suffers from label ambiguity, hindering discriminative feature learning.
• PATH: A Discrete-sequence Dataset for Evaluating Online Unsupervised Anomaly Detection Approaches for Multivariate Time Series
  21 Nov 2024 1 repository listed
  To cater for both unsupervised and semi-supervised anomaly detection settings, as well as time series generation and forecasting, we make different versions of the dataset available, where training and test subsets are…
• SADDE: Semi-supervised Anomaly Detection with Dependable Explanations
  18 Nov 2024 1 repository listed
  In this research paper, we introduce SADDE, a general framework designed to accomplish two primary objectives: (1) to render the anomaly detection process interpretable and enhance the credibility of interpretation…
• MTFL: Multi-Timescale Feature Learning for Weakly-Supervised Anomaly Detection in Surveillance Videos
  8 Oct 2024 1 repository listed
  Detection of anomaly events is relevant for public safety and requires a combination of fine-grained motion information and contextual events at variable time-scales.
• Self-supervised Anomaly Detection Pretraining Enhances Long-tail ECG Diagnosis
  30 Aug 2024 1 repository listed
  Current computer-aided ECG diagnostic systems struggle with the underdetection of rare but critical cardiac anomalies due to the imbalanced nature of ECG datasets.
• Multi-Normal Prototypes Learning for Weakly Supervised Anomaly Detection
  23 Aug 2024 1 repository listed
  Most of the existing methods assume the normal sample data clusters around a single central prototype while the real data may consist of multiple categories or subgroups.
• An AI System for Continuous Knee Osteoarthritis Severity Grading Using Self-Supervised Anomaly Detection with Limited Data
  16 Jul 2024 1 repository listed
  This work proposes a three stage approach for automated continuous grading of knee OA that is built upon the principles of Anomaly Detection (AD); learning a robust representation of healthy knee X-rays and grading…
• Infinite-dimensional Mahalanobis Distance with Applications to Kernelized Novelty Detection
  16 Jul 2024 1 repository listed
  Using the variance norm, we introduce the notion of a kernelized nearest-neighbour Mahalanobis distance.
• Deep Positive-Unlabeled Anomaly Detection for Contaminated Unlabeled Data
  29 May 2024 1 repository listed
  With our approach, we can approximate the anomaly scores for normal data using the unlabeled and anomaly data.
• Spatial-aware Attention Generative Adversarial Network for Semi-supervised Anomaly Detection in Medical Image
  21 May 2024 1 repository listed
  Medical anomaly detection is a critical research area aimed at recognizing abnormal images to aid in diagnosis.
• Semi-supervised Anomaly Detection via Adaptive Reinforcement Learning-Enabled Method with Causal Inference for Sensor Signals
  11 May 2024 1 repository listed
  The model leverages causal inference to extract the intrinsic causal feature in data, enhancing the agent's utilization of prior knowledge and improving its generalization capability.
• MAPL: Memory Augmentation and Pseudo-Labeling for Semi-Supervised Anomaly Detection
  10 May 2024 1 repository listed
  Meanwhile, a memory-enhanced learning mechanism is introduced to effectively predict abnormal regions by analyzing the difference be-tween the input samples and the normal samples in the memory pool.
• Machine learning-based identification of Gaia astrometric exoplanet orbits
  14 Apr 2024 1 repository listed
  We developed an alternative machine learning approach that uses only the Gaia DR3 orbital solutions with the aim of identifying the best candidates for exoplanets and brown-dwarf companions.

Syntology lines on 10 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.