“ 异常检测 ” 研究方向文章

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已看过的基于视频的异常检测研方向文章，继续更新中~~

Overview
Anomaly Detection : A Survey

Anomaly detection in dynamic networks: a survey

A Survey of Recent Trends in One Class Classification

A survey on unsupervised outlier detection in high‐dimensional numerical data

DEEP LEARNING FOR ANOMALY DETECTION: A SURVEY

An overview of deep learning based methods for unsupervised and semi-supervised anomaly detection in videos

Street Scene-A new dataset and evaluation protocol for video anomaly detection

Modeling Representation of Videos for Anomaly Detection using Deep Learning-A Review

Metrics, Techniques and Tools of Anomaly Detection-A Survey

A Survey of Video-Based Crowd Anomaly Detection in Desen Scenes

Classical Method
Isolation Forest

LOF: Identifying Density-Based Local Outliers

Extended Isolation Forest

Support Vector Method for Novelty Detection

One-Class Classification
One-Class SVMs for Document Classification

Support Vector Data Description

Can I Trust My One-Class Classification?

Efficient Anomaly Detection via Matrix Sketching

Deep One-Class Classification

High-dimensional and large-scale anomaly detection using a linear one-class SVM with deep learning

Optimal single-class classification strategies

Adversarially Learned One-Class Classifier for Novelty Detection

Learning Deep Features for One-Class Classification

Latent Space Autoregression for Novelty Detection

Generative Probabilistic Novelty Detection with Adversarial Autoencoders

PCA-based
robust deep and inductive anomaly detection

A loss framework for calibrated anomaly detection

Clustering
A Practical Algorithm for Distributed Clustering and Outlier Detection

Correlation
http://chaozhang.org/papers/cikm17a.pdf

Ranking
ranking causal anomalies via temporal and dynamical analysis on vanishing correlations

Auto-encoder
Learning sparse representation with variational auto-encoder for anomaly detection

Anomaly Detection with Robust Deep Autoencoders

DEEP AUTOENCODING GAUSSIAN MIXTURE MODEL FOR UNSUPERVISED ANOMALY DETECTION

Generative Probabilistic Novelty Detection with Adversarial Autoencoders

Split-Brain Autoencoders-Unsupervised Learning by Cross-Channel Prediction

Generative-probabilistic-novelty-detection-with-adversarial-autoencoders

Detecting anomalous events in videos by learning deep representations of appearance and motion

Abnormal Event Detection in Videos using Spatiotemporal Autoencoder

A study of deep convolutional auto-encoders for anomaly detection in videos

Learning Temporal Regularity in Video Sequences

DEEP AUTOENCODING GAUSSIAN MIXTURE MODEL FOR UNSUPERVISED ANOMALY DETECTION

Adversarial Autoencoders

Variational Auto-encoder
Multidimensional Time Series Anomaly Detection: A GRU-based Gaussian Mixture Variational Autoencoder Approach

A Multimodel Anomaly Detector for Robot-Assisted Feeding Using an LSTM-based Variational Autoencoder

Video Anomaly Detection and Localization via Gaussian Mixture Fully Convolutional Variational Autoencoder

GAN based
Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery

Efficient-GAN-Based Anomaly Detection

Anomaly detection with generative adversarial networks

Unsupervised Representation Learning With Deep Convolutional Generative Adversarial Networks

Training Adversarial Discriminators for Cross-channel Abnormal Event Detection in Crowds

GANomaly-Semi-Supervised Anomaly Detection via Adversarial Training

Future Frame Prediction for Anomaly Detection – A New Baseline

AVID-Adversarial Visual Irregularity Detection

Adversarially Learned One-Class Classifier for Novelty Detection

Abnormal Event Detection In Videos Using Generative Adversarial Nets

Unsupervised anomaly detection with generative adversarial networks

Hypersphereical Learning
Anomaly Detection in Dynamic Networks using Multi-view Time-Series Hypersphere Learning

Deep into Hypersphere: Robust and Unsupervised Anomaly Discovery in Dynamic Networks

Energy-based
Deep structured energy based models for anomaly detection

Time series
A Generalized Student-t Based Approach to Mixed-Type Anomaly Detection

Stochastic Online Anomaly Analysis for Streaming Time Series

Long short term memory networks for anmomaly detection in time series

LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection

Interpretation
Contextual Outlier Interpretation

Evaulation Metrics
Precision and Recall for Time Series

Geometric transformation
Deep Anomaly Detection Using Geometric Transformations

FeedBack
Incorporating Feedback into Tree-based Anomaly Detection

Feedback-Guided Anomaly Discovery via Online Optimization

群体异常检测类
Anomaly Detection in Video Using Predictive Convolutional Long Short-Term Memory Networks

Textures of Optical Flow for Real-Time Anomaly Detection in Crowds

Training Adversarial Discriminators for Cross-channel Abnormal Event Detection in Crowds

Textures of optical flow for real-time anomaly detection in crowds

Spatial–temporal convolutional neural networks for anomaly detection and localization in crowded scenes

Population Anomaly Detection through Deep Gaussianization

Plug-and-Play CNN for Crowd Motion Analysis-An Application in Abnormal Event Detection

Optimizing Interaction Force for Global Anomaly Detection in Crowded Scenes

Anomaly Detection in Crowded Scenes

【参考资料：】
https://github.com/zhuyiche/awesome-anomaly-detection

https://github.com/kc-ml2/journal-club/blob/ceaa45c5822f55d8060afdab907280d3e47b9288/past/2019-06-12-anomaly-detection.md

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