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Contents

Anomaly Detection

2023 Papers

WACV

  • Anomaly Clustering: Grouping Images Into Coherent Clusters of Anomaly Types (WACV 2023) [Paper]
    Datasets: MVTec dataset, magnetic tiledefect (MTD) dataset

  • No Shifted Augmentations (NSA): Compact Distributions for Robust Self-Supervised Anomaly Detection (WACV 2023) [Paper] [Code]
    Datasets: CIFAR10

  • Training Auxiliary Prototypical Classifiers for Explainable Anomaly Detection in Medical Image Segmentation (WACV 2023) [Paper]
    Datasets: magnetic resonance (MR), M&Ms challenge dataset, M&Ms-2, PROSTATEx, PROMISE12

  • Anomaly Detection in 3D Point Clouds Using Deep Geometric Descriptors (WACV 2023) [Paper]
    Datasets: MVTec 3D Anomaly Detection

  • Asymmetric Student-Teacher Networks for Industrial Anomaly Detection (WACV 2023) [Paper] [Code]
    Datasets: MVTec 3D Anomaly Detection

  • GLAD: A Global-to-Local Anomaly Detector (WACV 2023) [Paper]
    Datasets: MVTec

  • Zero-Shot Versus Many-Shot: Unsupervised Texture Anomaly Detection (WACV 2023) [Paper] [Code]
    Datasets: MVTec

  • Image-Consistent Detection of Road Anomalies As Unpredictable Patches (WACV 2023) [Paper]
    Datasets: Lost-and-Found(LaF), Road Anomaly (RA), Road Obstacles(RO) and Fishyscapes (FS), SegmentMeIfYouCan (SMIYC), CityScapes and BDD100k

2022 Papers

CVPR

  • Learning Second Order Local Anomaly for General Face Forgery Detection (CVPR 2022) [Paper]
    Datasets: Face-Forensics++ (FF++), Celeb-DF v2 (CD2), Deep-fakeDetection Dataset (DFD), and FaceShifter (Fshi)

ICML

  • Latent Outlier Exposure for Anomaly Detection with Contaminated Data (ICML 2022) [Paper] [Code]
    Datasets: CIFAR-10, Fashion-MNIST, MVTEC, 30 tabular data sets, UCSD Peds1

  • Deep Variational Graph Convolutional Recurrent Network for Multivariate Time Series Anomaly Detection (ICML 2022) [Paper] [Code]
    Datasets: DND, KPI, SMD, MSL, SMAP

  • FITNESS: (Fine Tune on New and Similar Samples) to detect anomalies in streams with drift and outliers (ICML 2022) [Paper] [Code]
    Datasets: Satellite and Thyroid, IoT Attack, Telemetry

  • Rethinking Graph Neural Networks for Anomaly Detection (ICML 2022) [Paper] [Code]
    Datasets: Amazon, YelpChi, T-Finance, T-Social

ECCV

  • Hierarchical Semi-Supervised Contrastive Learning for Contamination-Resistant Anomaly Detection (ECCV 2022) [Paper] [Code]
    Datasets: CIFAR-10, CIFAR-100, ImageNet (FIX), SVHN, and LSUN (FIX)

  • Locally Varying Distance Transform for Unsupervised Visual Anomaly Detection (ECCV 2022) [Paper] [Code]
    Datasets: MNIST; STL-10; Internet STL-10; MIT-Places-5; CIFAR-10; CatVsDog; Fashion-MNIST

  • Natural Synthetic Anomalies for Self-Supervised Anomaly Detection and Localization (ECCV 2022) [Paper] [Code]
    Datasets: MVTecAD; rCXR

  • DSR – A Dual Subspace Re-Projection Network for Surface Anomaly Detection (ECCV 2022) [Paper] [Code]
    Datasets: KSDD2; ImageNet

  • Pixel-Wise Energy-Biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes (ECCV 2022) [Paper] [Code]
    Datasets: LostAndFound; Fishyscapes; Road Anomaly

CVPRw

  • Autoencoders - A Comparative Analysis in the Realm of Anomaly Detection (CVPRw 2022) [Paper]
    Datasets: CIFAR10, MNIST

  • AnoDDPM: Anomaly Detection With Denoising Diffusion Probabilistic Models Using Simplex Noise (CVPRw 2022) [Paper] [Code]
    Datasets: MVTec AD

WACV

  • One-Class Learned Encoder-Decoder Network With Adversarial Context Masking for Novelty Detection (WACV 2022) [Paper] [Code]
    Datasets: MNIST, CIFAR-10, UCSD
    Task: Novelty Detection, Anomaly

  • CFLOW-AD: Real-Time Unsupervised Anomaly Detection With Localization via Conditional Normalizing Flows (WACV 2022) [Paper] [Code]
    Datasets: MVTec AD

  • Multi-Scale Patch-Based Representation Learning for Image Anomaly Detection and Segmentation (WACV 2022) [Paper]
    Datasets: MVTec AD, BTAD

BMVC

  • Anomaly Detection and Localization Using Attention-Guided Synthetic Anomaly and Test-Time Adaptation (BMVC 2022) [Paper]
    Datasets: MVTec AD, NIH

  • Siamese U-Net for Image Anomaly Detection and Segmentation with Contrastive Learning (BMVC 2022) [Paper]
    Datasets: MVTec AD, MVTec3D-AD

  • G-CMP: Graph-enhanced Contextual Matrix Profile for unsupervised anomaly detection in sensor-based remote health monitoring (BMVC 2022) [Paper]
    Datasets: Two real-world sensor-based remote health monitoringdatasets collected from the homes of persons living with dementia between August 2019 andApril 2022, by the UK Dementia Research Institute Care Research and Technology Centre

2021 Papers

CVPRw

  • Fuse-PN: A Novel Architecture for Anomaly Pattern Segmentation in Aerial Agricultural Images (CVPRw 2021) [Paper]

Older Papers

  • RaPP: Novelty Detection with Reconstruction along Projection Pathway (ICLR 2020) [Paper] [Code]
    Datasets: fMNIST, MNIST, MI-F and MI-V, STL, OTTO, SNSR, EOPT, NASA, RARM
    Task: Image Classification, Anomaly Detection

  • Interpretable, Multidimensional, Multimodal Anomaly Detection with Negative Sampling for Detection of Device Failure (ICML 2020) [Paper]
    Datasets: FOREST COVER(FC), MAMMOGRAPHY(MM), SMARTBUILDINGS(SB), MULCROSS(MC), SATELLITE(SA), SHUTTLE(SH)

  • Unsupervised Ensemble-Kernel Principal Component Analysis for Hyperspectral Anomaly Detection (CVPRw 2020) [Paper]

  • Superpixel Masking and Inpainting for Self-Supervised Anomaly Detection (BMVC 2020) [Paper]
    Datasets: MVTec AD

  • Deep Anomaly Detection with Outlier Exposure (ICLR 2019) [Paper] [Code]
    Datasets: CIFAR-10, CIFAR-100, Places, SST, SVHN, Tiny ImageNet, Tiny Images

  • Anomaly Detection With Multiple-Hypotheses Predictions (ICML 2019) [Paper]
    Datasets: CIFAR-10

  • Deep Anomaly Detection for Generalized Face Anti-Spoofing (CVPRw 2019) [Paper]

  • Anomaly-Based Manipulation Detection in Satellite Images (CVPRw 2019) [Paper]

  • Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection (ICLR 2018) [Paper] [Code]
    Datasets: CIFAR-10, Fashion-MNIST, MNIST, STL-10, cats_vs_dogs

  • Efficient Anomaly Detection via Matrix Sketching (NeurIPS 2018) [Paper]
    Datasets: p53 mutants, Dorothea and RCV1

  • Deep Anomaly Detection Using Geometric Transformations (NeurIPS 2018) [Paper] [Code]
    Datasets: CIFAR-10, CIFAR-100, CatsVsDogs, fashion-MNIST

  • A loss framework for calibrated anomaly detection (NeurIPS 2018) [Paper]

  • Towards Universal Representation for Unseen Action Recognition (CVPR 2018) [Paper]
    Datasets: ActivityNet, HMDB51 and UCF101
    Task: Action Recognition

Anomaly Detection Videos

2023 Papers

ICCV

  • Multimodal Motion Conditioned Diffusion Model for Skeleton-based Video Anomaly Detection (ICCV 2023) [Paper]

WACV

  • DyAnNet: A Scene Dynamicity Guided Self-Trained Video Anomaly Detection Network (WACV 2023) [Paper]
    Datasets: UCF-Crime, CCTV-Fights, UBI-Fights

  • Cross-Domain Video Anomaly Detection Without Target Domain Adaptation (WACV 2023) [Paper]
    Datasets: SHTdc, SHT and Ped2, HMDB, UCF101

  • Bi-Directional Frame Interpolation for Unsupervised Video Anomaly Detection (WACV 2023) [Paper]
    Datasets: UCSD Ped2, CUHK Avenue, ShanghaiTech Campus

  • Towards Interpretable Video Anomaly Detection (WACV 2023) [Paper]
    Datasets: CUHK Avenue, ShanghaiTech Campus

  • Normality Guided Multiple Instance Learning for Weakly Supervised Video Anomaly Detection (WACV 2023) [Paper]
    Datasets: ShanghaiTech, UCF-Crime, XD-Violence

2022 Papers

CVPR

  • UBnormal: New Benchmark for Supervised Open-Set Video Anomaly Detection (CVPR 2022) [Paper] [Code]
    Datasets: UBnormal, CHUK, Avenue, Shang-hai Tech

  • Deep Anomaly Discovery From Unlabeled Videos via Normality Advantage and Self-Paced Refinement (CVPR 2022) [Paper] [Code]
    Datasets: UCS-Dped1/UCSDped2, Avenue and ShanghaiTech

  • Self-Supervised Predictive Convolutional Attentive Block for Anomaly Detection (CVPR 2022) [Paper] [Code]
    Datasets: MVTec AD, Avenue and ShanghaiTech

  • Anomaly Detection via Reverse Distillation From One-Class Embedding (CVPR 2022) [Paper]
    Datasets: MVTec; MNIST, FashionMNIST and CIFAR10

  • Bayesian Nonparametric Submodular Video Partition for Robust Anomaly Detection (CVPR 2022) [Paper]
    Datasets: ShanghaiTech, Avenue, UCF-Crime

  • Towards Total Recall in Industrial Anomaly Detection (CVPR 2022) [Paper] [Code]
    Datasets: MVTec; Magnetic Tile Defects (MTD); Mini Shanghai Tech Campus(mSTC)

  • Generative Cooperative Learning for Unsupervised Video Anomaly Detection (CVPR 2022) [Paper] [Code]
    Datasets: UCF-Crime (UCFC); ShanghaiTech

ICML

  • Latent Outlier Exposure for Anomaly Detection with Contaminated Data (ICML 2022) [Paper] [Code]
    Datasets: CIFAR-10, Fashion-MNIST, MVTEC, 30 tabular data sets, UCSD Peds1

ECCV

  • Towards Open Set Video Anomaly Detection (ECCV 2022) [Paper]
    Datasets: XD Violence, UCF Crime, ShanghaiTech Campus

  • Scale-Aware Spatio-Temporal Relation Learning for Video Anomaly Detection (ECCV 2022) [Paper] [Code]
    Datasets: UCF-Crime (UCFC); ShanghaiTech

  • Dynamic Local Aggregation Network with Adaptive Clusterer for Anomaly Detection (ECCV 2022) [Paper] [Code]
    Datasets: CUHK Avenue; UCSD Ped2; ShanghaiTech

  • Video Anomaly Detection by Solving Decoupled Spatio-Temporal Jigsaw Puzzles (ECCV 2022) [Paper]
    Datasets: CUHK Avenue; UCSD Ped2; ShanghaiTech

  • Self-Supervised Sparse Representation for Video Anomaly Detection (ECCV 2022) [Paper] [Code]
    Datasets: ShanghaiTech, UCF-Crime, and XD-Violence

  • Registration Based Few-Shot Anomaly Detection (ECCV 2022) [Paper] [Code]
    Datasets: MVTec; MPDD

  • DenseHybrid: Hybrid Anomaly Detection for Dense Open-set Recognition (ECCV 2022) [Paper] [Code]
    Datasets: Fishyscapes, SegmentMeIfYouCan (SMIYC), StreetHazards

CVPRw

  • Unsupervised Anomaly Detection From Time-of-Flight Depth Images (CVPRw 2022) [Paper]
    Datasets: TIMo

  • Adversarial Machine Learning Attacks Against Video Anomaly Detection Systems (CVPRw 2022) [Paper]
    Datasets: CUHK Avenue, the ShanghaiTech Campus

  • Anomaly Detection in Autonomous Driving: A Survey (CVPRw 2022) [Paper]

WACV

  • A Modular and Unified Framework for Detecting and Localizing Video Anomalies (WACV 2022) [Paper]
    Datasets: CUHK Avenue, UCSD Ped2, ShanghaiTech Campus, UR fall

  • FastAno: Fast Anomaly Detection via Spatio-Temporal Patch Transformation (WACV 2022) [Paper]
    Datasets: CUHK Avenue, UCSD Ped2, ShanghaiTech Campus

  • Multi-Branch Neural Networks for Video Anomaly Detection in Adverse Lighting and Weather Conditions (WACV 2022) [Paper] [Code]
    Datasets: CUHK Avenue (Augmented)

  • Discrete Neural Representations for Explainable Anomaly Detection (WACV 2022) [Paper] [Code]
    Datasets: CUHK Avenue, UCSD Ped2, X-MAN

  • Rethinking Video Anomaly Detection - A Continual Learning Approach (WACV 2022) [Paper]
    Datasets: NOLA

2021 Papers

CVPRw

  • Box-Level Tube Tracking and Refinement for Vehicles Anomaly Detection (CVPRw 2021) [Paper]

  • Dual-Modality Vehicle Anomaly Detection via Bilateral Trajectory Tracing (CVPRw 2021) [Paper]

  • A Vision-Based System for Traffic Anomaly Detection Using Deep Learning and Decision Trees (CVPRw 2021) [Paper]

  • Good Practices and a Strong Baseline for Traffic Anomaly Detection (CVPRw 2021) [Paper]

  • An Efficient Approach for Anomaly Detection in Traffic Videos (CVPRw 2021) [Paper]

  • Spacecraft Time-Series Anomaly Detection Using Transfer Learning (CVPRw 2021) [Paper]

Older Papers

  • Multi-Granularity Tracking With Modularlized Components for Unsupervised Vehicles Anomaly Detection (CVPRw 2020) [Paper]

  • Fractional Data Distillation Model for Anomaly Detection in Traffic Videos (CVPRw 2020) [Paper]

  • Towards Real-Time Systems for Vehicle Re-Identification, Multi-Camera Tracking, and Anomaly Detection (CVPRw 2020) [Paper]

  • Fast Unsupervised Anomaly Detection in Traffic Videos (CVPRw 2020) [Paper]

  • Continual Learning for Anomaly Detection in Surveillance Videos (CVPRw 2020) [Paper]

  • Any-Shot Sequential Anomaly Detection in Surveillance Videos (CVPRw 2020) [Paper]

  • Challenges in Time-Stamp Aware Anomaly Detection in Traffic Videos (CVPRw 2019) [Paper]

  • Traffic Anomaly Detection via Perspective Map based on Spatial-temporal Information Matrix (CVPRw 2019) [Paper]

  • Unsupervised Traffic Anomaly Detection Using Trajectories (CVPRw 2019) [Paper]

  • Attention Driven Vehicle Re-identification and Unsupervised Anomaly Detection for Traffic Understanding (CVPRw 2019) [Paper]

  • A Comparative Study of Faster R-CNN Models for Anomaly Detection in 2019 AI City Challenge (CVPRw 2019) [Paper]

  • Anomaly Candidate Identification and Starting Time Estimation of Vehicles from Traffic Videos (CVPRw 2019) [Paper]

  • Hybrid Deep Network for Anomaly Detection (BMVC 2019) [Paper]
    Datasets: CUHK Avenue, UCSD Ped2, Belleview, Traffic-Train

  • Motion-Aware Feature for Improved Video Anomaly Detection (BMVC 2019) [Paper]
    Datasets: UCF Crime

  • Adversarially Learned One-Class Classifier for Novelty Detection (CVPR 2018) [Paper]
    Datasets: MNIST, Caltech-256, UCSD Ped2
    Task: Image Classification, Anomaly Detection

  • Real-World Anomaly Detection in Surveillance Videos (CVPR 2018) [Paper] [Code]
    Datasets: Real-world Surveillance Videos

  • Future Frame Prediction for Anomaly Detection – A New Baseline (CVPR 2018) [Paper] [Code]
    Datasets: CUHK, Avenue, UCSD Ped1, UCSD Ped2, ShanghaiTech, Paper's toy dataset

  • Unsupervised Anomaly Detection for Traffic Surveillance Based on Background Modeling (CVPRw 2018) [Paper]

  • Dual-Mode Vehicle Motion Pattern Learning for High Performance Road Traffic Anomaly Detection (CVPRw 2018) [Paper]