Hotpaper in 2021-2022 (Anomaly detection / Failure detection)
2023/03/10 00:00:00
2023/07/05 17:28:00
paper list
本文整理2021-2022的关注的各大主题的热门论文。记得读后及时做笔记！
❌——与本人研究不太相关
🌟——需要阅读
✅——已经阅读
| title | citation | conf | year | need read? | note | the point |
|---|---|---|---|---|---|---|
| Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning | 76 | TNNLS | 2022 | ❌ | link | 图神经网络，有监督 |
| CFLOW-AD: Real-Time Unsupervised Anomaly Detection With Localization via Conditional Normalizing Flows | 71 | WACV | 2022 | 🌟 | link | 无监督、实时、图像、归一化流 |
| Prior-Based Tensor Approximation for Anomaly Detection in Hyperspectral Imagery | 50 | TNNLS | 2022 | |||
| A Survey of Single-Scene Video Anomaly Detection | 48 | TPAMI | 2022 | |||
| Towards Total Recall in Industrial Anomaly Detection | 32 | CVPR | 2022 | 🌟 | link | 图像、p retrain model-based |
| Multipixel Anomaly Detection With Unknown Patterns for Hyperspectral Imagery | 30 | TNNLS | 2022 | |||
| Anomaly Detection in Quasi-Periodic Time Series Based on Automatic Data Segmentation and Attentional LSTM-CNN | 29 | TKDE | 2022 | ✅ | link | 准周期时间序列、分割、有监督 |
| Developing an Unsupervised Real-Time Anomaly Detection Scheme for Time Series With Multi-Seasonality | 26 | TKDE | 2022 | |||
| Anomaly Detection Based on Zero-Shot Outlier Synthesis and Hierarchical Feature Distillation | 26 | TNNLS | 2022 | ✅ | link | 异常样本的zeroshot合成：在正常分布的边缘采样 |
| Anomaly Explanation | 24 | IJCAI | 2022 | ✅ | Anomaly Explanation的四种分类方法以及简单比较： explanation by feature importance, feature values, data points comparisons,structure analysis. | |
| A Deep Multi-View Framework for Anomaly Detection on Attributed Networks | 24 | TKDE | 2022 | |||
| Feature Encoding With Autoencoders for Weakly Supervised Anomaly Detection | 22 | TNNLS | 2022 | 🤔️ | ||
| MOCCA: Multilayer One-Class Classification for Anomaly Detection | 21 | TNNLS | 2022 | 🌟 | ||
| Towards a Rigorous Evaluation of Time-Series Anomaly Detection | 20 | AAAI | 2022 | ✅ | link，CSDN | 现有的time series anomaly detection的F1评估体系高估了很多方法的性能，导致了不公平比较。本文建议使用PA%K，即标，而是与它们一起使用。PA%K的思想是仅当某个异常段中正确检测到的异常数量与其长度的比值超过了阈值K时，声明一个true positive。此外本文还提出了一种新基线测试方法。 |
| Robust Unsupervised Video Anomaly Detection by Multipath Frame Prediction | 19 | TNNLS | 2022 | |||
| A Synergistic Approach for Graph Anomaly Detection With Pattern Mining and Feature Learning | 19 | TNNLS | 2022 | |||
| Rethinking Video Anomaly Detection - A Continual Learning Approach | 19 | WACV | 2022 | |||
| Neural Contextual Anomaly Detection for Time Series | 16 | IJCAI | 2022 | ✅ | 1. 基于窗口的对比学习：异常会在嵌入上产生显著的扰动，所以当我们比较两个重叠段的表示时，如果一个包含异常，一个没有，我们期望它们是不同的；2. 利用数据增强方法：outlier exposure、mixup（提高泛化性） | |
| Anomaly Detection With Bidirectional Consistency in Videos | 16 | TNNLS | 2022 | |||
| Multi-Scale Patch-Based Representation Learning for Image Anomaly Detection and Segmentation | 14 | WACV | 2022 | |||
| Deep Graph-level Anomaly Detection by Glocal Knowledge Distillation | 13 | WSDM | 2022 | |||
| Pixel-Wise Energy-Biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes | 12 | ECCV | 2022 | |||
| Towards Continual Adaptation in Industrial Anomaly Detection | 12 | MM | 2022 | |||
| FastAno: Fast Anomaly Detection via Spatio-Temporal Patch Transformation | 12 | WACV | 2022 | 🌟 | ||
| Catching Both Gray and Black Swans: Open-Set Supervised Anomaly Detection | 11 | CVPR | 2022 | 🌟 | ||
| Self-Supervised Predictive Convolutional Attentive Block for Anomaly Detection | 10 | CVPR | 2022 | 🌟 | ||
| A Framework for Anomaly Detection in Time-Driven and Event-Driven Processes Using Kernel Traces | 10 | TKDE | 2022 | ❌ | link | 进程视角下的异常检测 |
| Beyond Dents and Scratches: Logical Constraints in Unsupervised Anomaly Detection and Localization | 9 | IJCV | 2022 | |||
| Cross-Domain Graph Anomaly Detection | 9 | TNNLS | 2022 | |||
| Weakly Supervised Discriminative Learning With Spectral Constrained Generative Adversarial Network for Hyperspectral Anomaly Detection | 9 | TNNLS | 2022 | |||
| Focus Your Distribution: Coarse-to-Fine Non-Contrastive Learning for Anomaly Detection and Localization | 8 | ICME | 2022 | |||
| Latent Outlier Exposure for Anomaly Detection with Contaminated Data | 8 | ICML | 2022 | 🌟 | ||
| Automated Anomaly Detection via Curiosity-Guided Search and Self-Imitation Learning | 8 | TNNLS | 2022 | |||
| Graph Regularized Autoencoder and its Application in Unsupervised Anomaly Detection | 8 | TPAMI | 2022 | |||
| Learning Task-Specific Representation for Video Anomaly Detection with Spatial-Temporal Attention | 7 | ICASSP | 2022 | |||
| Neighborhood Structure Assisted Non-negative Matrix Factorization and Its Application in Unsupervised Point-wise Anomaly Detection | 7 | JMLR | 2022 | |||
| An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series | 7 | TNNLS | 2022 | 🌟 | ||
| Discrete Neural Representations for Explainable Anomaly Detection | 7 | WACV | 2022 | ✅ | link | 两段式的异常解释方法：异常检测与定位、基于目标识别的异常解释 |
| Comprehensive Regularization in a Bi-directional Predictive Network for Video Anomaly Detection | 6 | AAAI | 2022 | |||
| Deep Generative model with Hierarchical Latent Factors for Time Series Anomaly Detection | 6 | AISTATS | 2022 | 🌟 | ||
| Natural Synthetic Anomalies for Self-supervised Anomaly Detection and Localization | 6 | ECCV | 2022 | 🌟 | ||
| Diffusion Models for Medical Anomaly Detection | 6 | MICCAI | 2022 | |||
| Local Anomaly Detection for Multivariate Time Series by Temporal Dependency Based on Poisson Model | 6 | TNNLS | 2022 | 🌟 | ||
| Multi-Branch Neural Networks for Video Anomaly Detection in Adverse Lighting and Weather Conditions | 6 | WACV | 2022 | |||
| A Causal Inference Look at Unsupervised Video Anomaly Detection | 5 | AAAI | 2022 | ✅ | link | 从因果推理的角度分析injected label的生成过程，并去除上述伪标签的影响 |
| DenseHybrid: Hybrid Anomaly Detection for Dense Open-Set Recognition | 5 | ECCV | 2022 | |||
| Deep Variational Graph Convolutional Recurrent Network for Multivariate Time Series Anomaly Detection | 5 | ICML | 2022 | 🌟 | 和后面的课题有关 | |
| Matrix Profile XXIV: Scaling Time Series Anomaly Detection to Trillions of Datapoints and Ultra-fast Arriving Data Streams | 5 | KDD | 2022 | |||
| Memory-Augmented Generative Adversarial Networks for Anomaly Detection | 5 | TNNLS | 2022 | |||
| Self-Training Multi-Sequence Learning with Transformer for Weakly Supervised Video Anomaly Detection | 4 | AAAI | 2022 | |||
| AnomalyKiTS: Anomaly Detection Toolkit for Time Series | 4 | AAAI | 2022 | |||
| DSR - A Dual Subspace Re-Projection Network for Surface Anomaly Detection | 4 | ECCV | 2022 | |||
| Raising the Bar in Graph-level Anomaly Detection | 4 | IJCAI | 2022 | |||
| Experimental Comparison and Survey of Twelve Time Series Anomaly Detection Algorithms (Extended Abstract) | 4 | IJCAI | 2022 | |||
| Local Evaluation of Time Series Anomaly Detection Algorithms | 4 | KDD | 2022 | 🌟 | ||
| AntiBenford Subgraphs: Unsupervised Anomaly Detection in Financial Networks | 4 | KDD | 2022 | 🌟 | 金融领域的异常检测，看看 | |
| Toolkit for Time Series Anomaly Detection | 4 | KDD | 2022 | |||
| Fast Unsupervised Brain Anomaly Detection and Segmentation with Diffusion Models | 4 | MICCAI | 2022 | |||
| Memorizing Structure-Texture Correspondence for Image Anomaly Detection | 4 | TNNLS | 2022 | |||
| Unsupervised Anomaly Detection by Robust Density Estimation | 3 | AAAI | 2022 | 🌟 | ||
| Transferring the Contamination Factor between Anomaly Detection Domains by Shape Similarity | 3 | AAAI | 2022 | |||
| Generative Cooperative Learning for Unsupervised Video Anomaly Detection | 3 | CVPR | 2022 | |||
| Video Anomaly Detection via Prediction Network with Enhanced Spatio-Temporal Memory Exchange | 3 | ICASSP | 2022 | |||
| Learning Appearance-Motion Normality for Video Anomaly Detection | 3 | ICME | 2022 | |||
| Anomaly Detection by Leveraging Incomplete Anomalous Knowledge with Anomaly-Aware Bidirectional GANs | 3 | IJCAI | 2022 | |||
| Reconstruction Enhanced Multi-View Contrastive Learning for Anomaly Detection on Attributed Networks | 3 | IJCAI | 2022 | |||
| GRELEN: Multivariate Time Series Anomaly Detection from the Perspective of Graph Relational Learning | 3 | IJCAI | 2022 | 🌟 | 可能和后面的课题有关 | |
| SmithNet: Strictness on Motion-Texture Coherence for Anomaly Detection | 3 | TNNLS | 2022 | |||
| Comparison of Anomaly Detectors: Context Matters | 3 | TNNLS | 2022 | |||
| Self-Supervised Acoustic Anomaly Detection Via Contrastive Learning | 2 | ICASSP | 2022 | |||
| CADET: Calibrated Anomaly Detection for Mitigating Hardness Bias | 2 | IJCAI | 2022 | |||
| HashNWalk: Hash and Random Walk Based Anomaly Detection in Hyperedge Streams | 2 | IJCAI | 2022 | |||
| SoftPatch: Unsupervised Anomaly Detection with Noisy Data | 2 | NIPS | 2022 | |||
| ComGA: Community-Aware Attributed Graph Anomaly Detection | 2 | WSDM | 2022 | |||
| TFAD: A Decomposition Time Series Anomaly Detection Architecture with Time-Frequency Analysis | 1 | CIKM | 2022 | 🌟 | 可解释性方面看一下 | |
| Self-supervision Meets Adversarial Perturbation: A Novel Framework for Anomaly Detection | 1 | CIKM | 2022 | 🌟 | 鲁棒异常检测？ | |
| UBnormal: New Benchmark for Supervised Open-Set Video Anomaly Detection | 1 | CVPR | 2022 | |||
| Detecting Anomaly in Chemical Sensors via Regularized Contrastive Learning | 1 | ICASSP | 2022 | |||
| Unsupervised Anomaly Detection for Container Cloud Via BILSTM-Based Variational Auto-Encoder | 1 | ICASSP | 2022 | |||
| Multiple Temporal Context Embedding Networks for Unsupervised time Series Anomaly Detection | 1 | ICASSP | 2022 | |||
| Improving Anomaly Detection with a Self-Supervised Task Based on Generative Adversarial Network | 1 | ICASSP | 2022 | |||
| Controlled Sensing and Anomaly Detection Via Soft Actor-Critic Reinforcement Learning | 1 | ICASSP | 2022 | |||
| Object-Guided and Motion-Refined Attention Network for Video Anomaly Detection | 1 | ICME | 2022 | |||
| Multi-Scale Continuity-Aware Refinement Network for Weakly Supervised Video Anomaly Detection | 1 | ICME | 2022 | |||
| Rethinking Graph Neural Networks for Anomaly Detection | 1 | ICML | 2022 | |||
| Constrained Adaptive Projection with Pretrained Features for Anomaly Detection | 1 | IJCAI | 2022 | 🌟 | ||
| PAC-Wrap: Semi-Supervised PAC Anomaly Detection | 1 | KDD | 2022 | 🌟 | ||
| RCAD: Real-time Collaborative Anomaly Detection System for Mobile Broadband Networks | 1 | KDD | 2022 | 🌟 | 移动宽带异常检测，可能和后面的课题有关 | |
| Dynamic Network Anomaly Modeling of Cell-Phone Call Detail Records for Infectious Disease Surveillance | 1 | KDD | 2022 | 🌟 | 后面的课题相关 | |
| Dual-Distribution Discrepancy for Anomaly Detection in Chest X-Rays | 1 | MICCAI | 2022 | |||
| Pixel-Level Anomaly Detection via Uncertainty-aware Prototypical Transformer | 1 | MM | 2022 | |||
| Hierarchical Scene Normality-Binding Modeling for Anomaly Detection in Surveillance Videos | 1 | MM | 2022 | |||
| Graph Convolutional Adversarial Networks for Spatiotemporal Anomaly Detection | 1 | TNNLS | 2022 | |||
| Semisupervised Training of Deep Generative Models for High-Dimensional Anomaly Detection | 1 | TNNLS | 2022 | |||
| Attract-Repel Encoder: Learning Anomaly Representation Away From Landmarks | 1 | TNNLS | 2022 | 🌟 | ||
| Center-Aware Adversarial Autoencoder for Anomaly Detection | 1 | TNNLS | 2022 | 🌟 | ||
| A Semi-Supervised VAE Based Active Anomaly Detection Framework in Multivariate Time Series for Online Systems | 1 | WWW | 2022 | 🌟 | ||
| CCA: An ML Pipeline for Cloud Anomaly Troubleshooting | 0 | AAAI | 2022 | |||
| Learning Hypersphere for Few-shot Anomaly Detection on Attributed Networks | 0 | CIKM | 2022 | |||
| Towards an Awareness of Time Series Anomaly Detection Models’ Adversarial Vulnerability | 0 | CIKM | 2022 | |||
| Bayesian Nonparametric Submodular Video Partition for Robust Anomaly Detection | 0 | CVPR | 2022 | |||
| Learning Second Order Local Anomaly for General Face Forgery Detection | 0 | CVPR | 2022 | |||
| Hierarchical Semi-supervised Contrastive Learning for Contamination-Resistant Anomaly Detection | 0 | ECCV | 2022 | |||
| Approaches Toward Physical and General Video Anomaly Detection | 0 | ICASSP | 2022 | |||
| Dictionary Learning with Uniform Sparse Representations for Anomaly Detection | 0 | ICASSP | 2022 | |||
| An Anomaly Detection Method Based on Self-Supervised Learning with Soft Label Assignment for Defect Visual Inspection | 0 | ICASSP | 2022 | |||
| Contrastive Predictive Coding for Anomaly Detection of Fetal Health from the Cardiotocogram | 0 | ICASSP | 2022 | |||
| Stgat-Mad : Spatial-Temporal Graph Attention Network For Multivariate Time Series Anomaly Detection | 0 | ICASSP | 2022 | |||
| A Closer Look at Autoencoders for Unsupervised Anomaly Detection | 0 | ICASSP | 2022 | |||
| Integration of Anomaly Machine Sound Detection into Active Noise Control to Shape the Residual Sound | 0 | ICASSP | 2022 | |||
| Just Noticeable Learning for Unsupervised Anomaly Localization and Detection | 0 | ICME | 2022 | |||
| Domain-Generalized Textured Surface Anomaly Detection | 0 | ICME | 2022 | |||
| Locality-Aware Attention Network with Discriminative Dynamics Learning for Weakly Supervised Anomaly Detection | 0 | ICME | 2022 | |||
| Understanding and Mitigating Data Contamination in Deep Anomaly Detection: A Kernel-based Approach | 0 | IJCAI | 2022 | |||
| Framing Algorithmic Recourse for Anomaly Detection | 0 | KDD | 2022 | |||
| Subset Node Anomaly Tracking over Large Dynamic Graphs | 0 | KDD | 2022 | |||
| Adaptive Model Pooling for Online Deep Anomaly Detection from a Complex Evolving Data Stream | 0 | KDD | 2022 | |||
| Augmenting Log-based Anomaly Detection Models to Reduce False Anomalies with Human Feedback | 0 | KDD | 2022 | |||
| Anomaly Detection for Spatiotemporal Data in Action | 0 | KDD | 2022 | |||
| A Multi-task Network with Weight Decay Skip Connection Training for Anomaly Detection in Retinal Fundus Images | 0 | MICCAI | 2022 | |||
| Task-Oriented Self-supervised Learning for Anomaly Detection in Electroencephalography | 0 | MICCAI | 2022 | |||
| Anomaly-Aware Multiple Instance Learning for Rare Anemia Disorder Classification | 0 | MICCAI | 2022 | |||
| Evidential Reasoning for Video Anomaly Detection | 0 | MM | 2022 | |||
| Purifier: Plug-and-play Backdoor Mitigation for Pre-trained Models Via Anomaly Activation Suppression | 0 | MM | 2022 | |||
| Anomaly Warning: Learning and Memorizing Future Semantic Patterns for Unsupervised Ex-ante Potential Anomaly Prediction | 0 | MM | 2022 | |||
| Few-Shot Fast-Adaptive Anomaly Detection | 0 | NIPS | 2022 | |||
| Perturbation Learning Based Anomaly Detection | 0 | NIPS | 2022 | |||
| GraphAD: A Graph Neural Network for Entity-Wise Multivariate Time-Series Anomaly Detection | 0 | SIGIR | 2022 | |||
| Leveraging World Events to Predict E-Commerce Consumer Demand under Anomaly | 0 | WSDM | 2022 | |||
| MemStream: Memory-Based Streaming Anomaly Detection | 0 | WWW | 2022 | |||
| Towards Open Set Video Anomaly Detection | -1 | ECCV | 2022 | |||
| Anomaly Detection for Tabular Data with Internal Contrastive Learning | -1 | ICLR | 2022 | |||
| Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series | -1 | ICLR | 2022 | |||
| Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy | -1 | ICLR | 2022 | |||
| Learning Sparse Latent Graph Representations for Anomaly Detection in Multivariate Time Series | -1 | KDD | 2022 | |||
| CAT: Beyond Efficient Transformer for Content-Aware Anomaly Detection in Event Sequences | -1 | KDD | 2022 | |||
| ANDEA: Anomaly and Novelty Detection, Explanation, and Accommodation | -1 | KDD | 2022 | |||
| Dual-discriminative Graph Neural Network for Imbalanced Graph-level Anomaly Detection | -1 | NIPS | 2022 | |||
| Unsupervised Contextual Anomaly Detection for Database Systems | -1 | SIGMOD | 2022 | |||
| Editorial Deep Learning for Anomaly Detection | -1 | TNNLS | 2022 | |||
| CutPaste: Self-Supervised Learning for Anomaly Detection and Localization | 228 | CVPR | 2021 | |||
| Anomaly Detection in Video via Self-Supervised and Multi-Task Learning | 116 | CVPR | 2021 | |||
| The MVTec Anomaly Detection Dataset: A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection | 112 | IJCV | 2021 | |||
| Video Anomaly Detection with Sparse Coding Inspired Deep Neural Networks | 107 | TPAMI | 2021 | |||
| PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation | 98 | CVPR | 2021 | |||
| DRAEM - A Discriminatively Trained Reconstruction Embedding for Surface Anomaly Detection | 84 | ICCV | 2021 | |||
| Anomaly Detection of Time Series With Smoothness-Inducing Sequential Variational Auto-Encoder | 69 | TNNLS | 2021 | |||
| Graph Neural Network-Based Anomaly Detection in Multivariate Time Series | 66 | AAAI | 2021 | |||
| MIST: Multiple Instance Self-Training Framework for Video Anomaly Detection | 56 | CVPR | 2021 | |||
| Multiresolution Knowledge Distillation for Anomaly Detection | 49 | CVPR | 2021 | |||
| Pixel-Wise Anomaly Detection in Complex Driving Scenes | 47 | CVPR | 2021 | |||
| Weakly-Supervised Video Anomaly Detection With Robust Temporal Feature Magnitude Learning | 40 | ICCV | 2021 | |||
| Driver Anomaly Detection: A Dataset and Contrastive Learning Approach | 40 | WACV | 2021 | |||
| Real-Time Nonparametric Anomaly Detection in High-Dimensional Settings | 39 | TPAMI | 2021 | |||
| A Hybrid Video Anomaly Detection Framework via Memory-Augmented Flow Reconstruction and Flow-Guided Frame Prediction | 38 | ICCV | 2021 | |||
| Toward Deep Supervised Anomaly Detection: Reinforcement Learning from Partially Labeled Anomaly Data | 35 | KDD | 2021 | |||
| Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs | 34 | CIKM | 2021 | |||
| Neural Transformation Learning for Deep Anomaly Detection Beyond Images | 31 | ICML | 2021 | |||
| Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images | 30 | MICCAI | 2021 | |||
| Appearance-Motion Memory Consistency Network for Video Anomaly Detection | 28 | AAAI | 2021 | |||
| Decoupling Representation Learning and Classification for GNN-based Anomaly Detection | 28 | SIGIR | 2021 | |||
| Glancing at the Patch: Anomaly Localization With Global and Local Feature Comparison | 27 | CVPR | 2021 | |||
| Few-shot Network Anomaly Detection via Cross-network Meta-learning | 26 | WWW | 2021 | |||
| Learning Causal Temporal Relation and Feature Discrimination for Anomaly Detection | 25 | TIP | 2021 | |||
| MStream: Fast Anomaly Detection in Multi-Aspect Streams | 25 | WWW | 2021 | |||
| G2D: Generate to Detect Anomaly | 22 | WACV | 2021 | |||
| F-FADE: Frequency Factorization for Anomaly Detection in Edge Streams | 22 | WSDM | 2021 | |||
| Learning Semantic Context from Normal Samples for Unsupervised Anomaly Detection | 21 | AAAI | 2021 | |||
| Convolutional Transformer based Dual Discriminator Generative Adversarial Networks for Video Anomaly Detection | 21 | MM | 2021 | |||
| A Hierarchical Transformation-Discriminating Generative Model for Few Shot Anomaly Detection | 20 | ICCV | 2021 | |||
| FluxEV: A Fast and Effective Unsupervised Framework for Time-Series Anomaly Detection | 20 | WSDM | 2021 | |||
| Deep Learning for Anomaly Detection: Challenges, Methods, and Opportunities | 20 | WSDM | 2021 | |||
| Divide-and-Assemble: Learning Block-Wise Memory for Unsupervised Anomaly Detection | 19 | ICCV | 2021 | |||
| ANEMONE: Graph Anomaly Detection with Multi-Scale Contrastive Learning | 18 | CIKM | 2021 | |||
| Multi-Scale One-Class Recurrent Neural Networks for Discrete Event Sequence Anomaly Detection | 18 | KDD | 2021 | |||
| Anomaly Detection in Time Series: A Comprehensive Evaluation | 18 | VLDB | 2021 | |||
| Multivariate Time Series Anomaly Detection and Interpretation using Hierarchical Inter-Metric and Temporal Embedding | 17 | KDD | 2021 | |||
| Deep Unsupervised Anomaly Detection | 17 | WACV | 2021 | |||
| SDFVAE: Static and Dynamic Factorized VAE for Anomaly Detection of Multivariate CDN KPIs | 17 | WWW | 2021 | |||
| GAN Ensemble for Anomaly Detection | 16 | AAAI | 2021 | |||
| Dance With Self-Attention: A New Look of Conditional Random Fields on Anomaly Detection in Videos | 16 | ICCV | 2021 | |||
| TSB-UAD: An End-to-End Benchmark Suite for Univariate Time-Series Anomaly Detection | 15 | VLDB | 2021 | |||
| Time Series Anomaly Detection with Multiresolution Ensemble Decoding | 14 | AAAI | 2021 | |||
| Weakly-Supervised Spatio-Temporal Anomaly Detection in Surveillance Video | 14 | IJCAI | 2021 | |||
| Masked Contrastive Learning for Anomaly Detection | 14 | IJCAI | 2021 | |||
| Transfer-Based Semantic Anomaly Detection | 13 | ICML | 2021 | |||
| Understanding the Effect of Bias in Deep Anomaly Detection | 13 | IJCAI | 2021 | |||
| LREN: Low-Rank Embedded Network for Sample-Free Hyperspectral Anomaly Detection | 12 | AAAI | 2021 | |||
| Road Anomaly Detection by Partial Image Reconstruction With Segmentation Coupling | 11 | ICCV | 2021 | |||
| Time Series Anomaly Detection for Cyber-physical Systems via Neural System Identification and Bayesian Filtering | 11 | KDD | 2021 | |||
| Toward Explainable Deep Anomaly Detection | 11 | KDD | 2021 | |||
| Elsa: Energy-based Learning for Semi-supervised Anomaly Detection | 10 | BMVC | 2021 | |||
| Practical Approach to Asynchronous Multivariate Time Series Anomaly Detection and Localization | 10 | KDD | 2021 | |||
| Online Anomaly Detection With Bandwidth Optimized Hierarchical Kernel Density Estimators | 10 | TNNLS | 2021 | |||
| ASC-Net: Adversarial-Based Selective Network for Unsupervised Anomaly Segmentation | 9 | MICCAI | 2021 | |||
| Unsupervised Cross-system Log Anomaly Detection via Domain Adaptation | 8 | CIKM | 2021 | |||
| Online false discovery rate control for anomaly detection in time series | 8 | NIPS | 2021 | |||
| Action Sequence Augmentation for Early Graph-based Anomaly Detection | 7 | CIKM | 2021 | |||
| Implicit Field Learning for Unsupervised Anomaly Detection in Medical Images | 7 | MICCAI | 2021 | |||
| Regularizing Attention Networks for Anomaly Detection in Visual Question Answering | 6 | AAAI | 2021 | |||
| Anomaly Mining: Past, Present and Future | 6 | CIKM | 2021 | |||
| Subtractive Aggregation for Attributed Network Anomaly Detection | 6 | CIKM | 2021 | |||
| An Accuracy Network Anomaly Detection Method Based on Ensemble Model | 6 | ICASSP | 2021 | |||
| Anomaly Mining - Past, Present and Future | 6 | IJCAI | 2021 | |||
| (1 + epsilon)-class Classification: an Anomaly Detection Method for Highly Imbalanced or Incomplete Data Sets | 6 | JMLR | 2021 | |||
| ELITE: Robust Deep Anomaly Detection with Meta Gradient | 6 | KDD | 2021 | |||
| Robust Graph Autoencoder for Hyperspectral Anomaly Detection | 5 | ICASSP | 2021 | |||
| Real-Time Synchronization in Neural Networks for Multivariate Time Series Anomaly Detection | 5 | ICASSP | 2021 | |||
| RCA: A Deep Collaborative Autoencoder Approach for Anomaly Detection | 5 | IJCAI | 2021 | |||
| Anomaly Attribution with Likelihood Compensation | 4 | AAAI | 2021 | |||
| Student-Teacher Feature Pyramid Matching for Anomaly Detection | 4 | BMVC | 2021 | |||
| Towards Anomaly-resistant Graph Neural Networks via Reinforcement Learning | 4 | CIKM | 2021 | |||
| Voting-Based Ensemble Model for Network Anomaly Detection | 4 | ICASSP | 2021 | |||
| A Semantic-Enhanced Method Based On Deep SVDD for Pixel-Wise Anomaly Detection | 4 | ICME | 2021 | |||
| TranAD: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series Data | 4 | VLDB | 2021 | |||
| Volume Under the Surface: A New Accuracy Evaluation Measure for Time-Series Anomaly Detection | 4 | VLDB | 2021 | |||
| Fourier Transformation Autoencoders for Anomaly Detection | 3 | ICASSP | 2021 | |||
| STEP-GAN: A One-Class Anomaly Detection Model with Applications to Power System Security | 3 | ICASSP | 2021 | |||
| Learning Discriminative Features for Semi-Supervised Anomaly Detection | 3 | ICASSP | 2021 | |||
| Towards Parkinson’s Disease Prognosis Using Self-Supervised Learning and Anomaly Detection | 3 | ICASSP | 2021 | |||
| Weakly Supervised Temporal Anomaly Segmentation With Dynamic Time Warping | 3 | ICCV | 2021 | |||
| Learning Unsupervised Metaformer for Anomaly Detection | 3 | ICCV | 2021 | |||
| Anomaly Detection with Prototype-Guided Discriminative Latent Embeddings | 3 | ICDM | 2021 | |||
| Near-Optimal Entrywise Anomaly Detection for Low-Rank Matrices with Sub-Exponential Noise | 3 | ICML | 2021 | |||
| Multiclass Anomaly Detector: the CS++ Support Vector Machine | 3 | JMLR | 2021 | |||
| SVD-GAN for Real-Time Unsupervised Video Anomaly Detection | 2 | BMVC | 2021 | |||
| Looking at the whole picture: constrained unsupervised anomaly segmentation | 2 | BMVC | 2021 | |||
| Low-Rank on Graphs Plus Temporally Smooth Sparse Decomposition for Anomaly Detection in Spatiotemporal Data | 2 | ICASSP | 2021 | |||
| Hybrid Model for Network Anomaly Detection with Gradient Boosting Decision Trees and Tabtransformer | 2 | ICASSP | 2021 | |||
| Situational Anomaly Detection in Multimedia Data under Concept Drift | 2 | MM | 2021 | |||
| ESAD: End-to-end Semi-supervised Anomaly Detection | 1 | BMVC | 2021 | |||
| TADPOLE: Task ADapted Pre-Training via AnOmaLy DEtection | 1 | EMNLP | 2021 | |||
| Cross-Scene Person Trajectory Anomaly Detection Based on Re-Identification | 1 | ICME | 2021 | |||
| Anomaly and Novelty Detection, Explanation, and Accommodation (ANDEA) | 1 | KDD | 2021 | |||
| Airway Anomaly Detection by Prototype-Based Graph Neural Network | 1 | MICCAI | 2021 | |||
| A New Distributional Treatment for Time Series and An Anomaly Detection Investigation | 1 | VLDB | 2021 | |||
| TimeEval: A Benchmarking Toolkit for Time Series Anomaly Detection Algorithms | 1 | VLDB | 2021 | |||
| Theseus: Navigating the Labyrinth of Time-Series Anomaly Detection | 1 | VLDB | 2021 | |||
| Sequential Adversarial Anomaly Detection with Deep Fourier Kernel | 0 | ICASSP | 2021 | |||
| Adversarial Regularized Reconstruction for Anomaly Detection and Generation | 0 | ICDM | 2021 | |||
| A Demonstration of AutoOD: A Self-tuning Anomaly Detection System | 0 | VLDB | 2021 | |||
| USAD: UnSupervised Anomaly Detection on Multivariate Time Series | 231 | KDD | 2020 | ✅ | link | auto-encoder+对抗损失 |
| Kitsune: An Ensemble of Autoencoders for Online Network Intrusion Detection | 763 | Machine Learning | 2018 | ✅ | link | 一种网络异常检测框架，在工程实现角度上的可借鉴之处很多 |