Anomaly Detection

Description from the archive archive 2025-07-28; Papers-with-Code links inside it are rewritten to this site.

Benchmarks archive 2025-07-28

76 leaderboard tables shown for this task, 76 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. 10 shown of 76 until expanded.

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

119 datasets whose archive record lists this task, ordered by the archive's paper count. 30 shown of 119 until expanded.

Subtasks archive 2025-07-28

28 subtasks in the archive's task tree.

Most implemented papers archive 2025-07-28

30 shown of 1,727 papers with code (4,856 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.

• Auto-Encoding Variational Bayes
  20 Dec 2013 144 repositories listed Syntology ran 112 of 199 samples · 87 unverified · 103 pointer-only (licence)
  First, we show that a reparameterization of the variational lower bound yields a lower bound estimator that can be straightforwardly optimized using standard stochastic gradient methods.
• EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level Latencies
  25 Mar 2023 33 repositories listed Syntology ran 1 of 35 samples · 34 unverified
  We train a student network to predict the extracted features of normal, i.
• PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization
  17 Nov 2020 26 repositories listed Syntology ran 7 of 7 samples · 0 unverified · 3 pointer-only (licence)
  We present a new framework for Patch Distribution Modeling, PaDiM, to concurrently detect and localize anomalies in images in a one-class learning setting.
• Towards Total Recall in Industrial Anomaly Detection
  15 Jun 2021 18 repositories listed Syntology ran 5 of 36 samples · 31 unverified
  Being able to spot defective parts is a critical component in large-scale industrial manufacturing.
• Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery
  17 Mar 2017 18 repositories listed Syntology ran 3 of 11 samples · 8 unverified · 3 pointer-only (licence)
  Obtaining models that capture imaging markers relevant for disease progression and treatment monitoring is challenging.
• Is Space-Time Attention All You Need for Video Understanding?
  9 Feb 2021 16 repositories listed Syntology ran 35 of 43 samples · 8 unverified · 14 pointer-only (licence)
  We present a convolution-free approach to video classification built exclusively on self-attention over space and time.
• A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
  7 Oct 2016 14 repositories listed Syntology ran 7 of 21 samples · 14 unverified · 6 pointer-only (licence)
  We consider the two related problems of detecting if an example is misclassified or out-of-distribution.
• DeepWalk: Online Learning of Social Representations
  26 Mar 2014 14 repositories listed Syntology ran 2 of 3 samples · 1 unverified · 1 pointer-only (licence)
  We present DeepWalk, a novel approach for learning latent representations of vertices in a network.
• Transformers in Time Series: A Survey
  15 Feb 2022 11 repositories listed
  From the perspective of network structure, we summarize the adaptations and modifications that have been made to Transformers in order to accommodate the challenges in time series analysis.
• MURA: Large Dataset for Abnormality Detection in Musculoskeletal Radiographs
  11 Dec 2017 11 repositories listed Syntology ran 1 of 1 samples · 0 unverified
  To evaluate models robustly and to get an estimate of radiologist performance, we collect additional labels from six board-certified Stanford radiologists on the test set, consisting of 207 musculoskeletal studies.
• Are Transformers Effective for Time Series Forecasting?
  26 May 2022 10 repositories listed Syntology ran 13 of 19 samples · 6 unverified · 13 pointer-only (licence)
  Recently, there has been a surge of Transformer-based solutions for the long-term time series forecasting (LTSF) task.
• Student-Teacher Feature Pyramid Matching for Anomaly Detection
  7 Mar 2021 10 repositories listed
  Anomaly detection is a challenging task and usually formulated as an one-class learning problem for the unexpectedness of anomalies.
• Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholding
  13 Feb 2018 10 repositories listed
  As spacecraft send back increasing amounts of telemetry data, improved anomaly detection systems are needed to lessen the monitoring burden placed on operations engineers and reduce operational risk.
• Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications
  12 Feb 2018 10 repositories listed
  To ensure undisrupted business, large Internet companies need to closely monitor various KPIs (e.
• Deep Anomaly Detection with Outlier Exposure
  11 Dec 2018 9 repositories listed Syntology ran 5 of 5 samples · 0 unverified · 4 pointer-only (licence)
  We also analyze the flexibility and robustness of Outlier Exposure, and identify characteristics of the auxiliary dataset that improve performance.
• Real-world Anomaly Detection in Surveillance Videos
  12 Jan 2018 9 repositories listed Syntology ran 4 of 6 samples · 2 unverified · 4 pointer-only (licence)
  To avoid annotating the anomalous segments or clips in training videos, which is very time consuming, we propose to learn anomaly through the deep multiple instance ranking framework by leveraging weakly labeled…
• GluonTS: Probabilistic Time Series Models in Python
  12 Jun 2019 8 repositories listed Syntology ran 0 of 18 samples · 18 unverified
  We introduce Gluon Time Series (GluonTS, available at https://gluon-ts.
• 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…
• LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection
  1 Jul 2016 8 repositories listed Syntology ran 1 of 9 samples · 8 unverified
  Mechanical devices such as engines, vehicles, aircrafts, etc., are typically instrumented with numerous sensors to capture the behavior and health of the machine.
• ToyADMOS2: Another dataset of miniature-machine operating sounds for anomalous sound detection under domain shift conditions
  4 Jun 2021 7 repositories listed
  This paper proposes a new large-scale dataset called "ToyADMOS2" for anomaly detection in machine operating sounds (ADMOS).
• 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.
• Efficient GAN-Based Anomaly Detection
  17 Feb 2018 7 repositories listed Syntology ran 4 of 15 samples · 11 unverified · 3 pointer-only (licence)
  However, few works have explored the use of GANs for the anomaly detection task.
• Deep Sets
  10 Mar 2017 7 repositories listed Syntology ran 9 of 12 samples · 3 unverified · 9 pointer-only (licence)
  Our main theorem characterizes the permutation invariant functions and provides a family of functions to which any permutation invariant objective function must belong.
• Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters
  19 Aug 2020 6 repositories listed Syntology ran 1 of 17 samples · 16 unverified
  Finally, the selected neighbors across different relations are aggregated together.
• Learning Generalized Spoof Cues for Face Anti-spoofing
  8 May 2020 6 repositories listed
  In this paper, we reformulate FAS in an anomaly detection perspective and propose a residual-learning framework to learn the discriminative live-spoof differences which are defined as the spoof cues.
• Deep Anomaly Detection with Deviation Networks
  19 Nov 2019 6 repositories listed
  Instead of representation learning, our method fulfills an end-to-end learning of anomaly scores by a neural deviation learning, in which we leverage a few (e.
• Deep and Confident Prediction for Time Series at Uber
  6 Sep 2017 6 repositories listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)
  Reliable uncertainty estimation for time series prediction is critical in many fields, including physics, biology, and manufacturing.
• PyPOTS: A Python Toolbox for Data Mining on Partially-Observed Time Series
  30 May 2023 5 repositories listed Syntology ran 0 of 21 samples · 21 unverified
  PyPOTS is an open-source Python library dedicated to data mining and analysis on multivariate partially-observed time series, i.
• Long-term Forecasting with TiDE: Time-series Dense Encoder
  17 Apr 2023 5 repositories listed Syntology ran 0 of 3 samples · 3 unverified
  Recent work has shown that simple linear models can outperform several Transformer based approaches in long term time-series forecasting.
• ADBench: Anomaly Detection Benchmark
  19 Jun 2022 5 repositories listed Syntology ran 0 of 1 samples · 1 unverified
  Given a long list of anomaly detection algorithms developed in the last few decades, how do they perform with regard to (i) varying levels of supervision, (ii) different types of anomalies, and (iii) noisy and corrupted…

Syntology lines on 23 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.