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We aim at constructing a high performance model for defect detection that detects unknown anomalous patterns of an image without anomalous data.
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Alexandre B Tsybakov · 2008
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Anomaly detection: A survey
Varun Chandola, Arindam Banerjee, and Vipin Kumar · 2009
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Alex Krizhevsky · 2009
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Diego Carrera, Giacomo Boracchi, Alessandro Foi, and Brendt Wohlberg · 2015
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Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Mehdi Noroozi and Paolo Favaro · 2016
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Philipp Seeböck, Sebastian Waldstein, Sophie Klimscha, Bianca S Gerendas, René Donner, Thomas Schlegl, Ursula Schmidt-Erfurth, and Georg Langs · 2016
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Improved regularization of convolutional neural networks with cutout
Terrance DeVries and Graham W Taylor · 2017
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Ilya Loshchilov and Frank Hutter · 2017
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dsprites: Disentanglement testing sprites dataset
Loic Matthey, Irina Higgins, Demis Hassabis, and Alexander Lerchner · 2017
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Unsupervised anomaly detection with generative adversarial networks to guide marker discovery
Thomas Schlegl, Philipp Seeböck, Sebastian M Waldstein, Ursula Schmidt-Erfurth, and Georg Langs · 2017
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Grad-cam: Visual explanations from deep networks via gradient-based localization
Ramprasaath R Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra · 2017
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MixUp: Beyond empirical risk minimization
Hongyi Zhang, Moustapha Cisse, Yann N. Dauphin, and David Lopez-Paz · 2017
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Ganomaly: Semi-supervised anomaly detection via adversarial training
Samet Akcay, Amir Atapour-Abarghouei, and Toby P Breckon · 2018
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Improving unsupervised defect segmentation by applying structural similarity to autoencoders
Paul Bergmann, Sindy Löwe, Michael Fauser, David Sattlegger, and Carsten Steger · 2018
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Deep clustering for unsupervised learning of visual features
Mathilde Caron, Piotr Bojanowski, Armand Joulin, and Matthijs Douze · 2018
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Waic, but why? generative ensembles for robust anomaly detection
Hyunsun Choi, Eric Jang, and Alexander A Alemi · 2018
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Unsupervised representation learning by predicting image rotations
Spyros Gidaris, Praveer Singh, and Nikos Komodakis · 2018
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Unsupervised embedding learning via invariant and spreading instance feature
Mang Ye, Xu Zhang, Pong C Yuen, and Shih-Fu Chang · 2019
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Cutmix: Regularization strategy to train strong classifiers with localizable features
Sangdoo Yun, Dongyoon Han, Seong Joon Oh, Sanghyuk Chun, Junsuk Choe, and Youngjoon Yoo · 2019
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Classification-based anomaly detection for general data
Liron Bergman and Yedid Hoshen · 2020
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Uninformed students: Student-teacher anomaly detection with discriminative latent embeddings
Paul Bergmann, Michael Fauser, David Sattlegger, and Carsten Steger · 2020
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
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Dan Hendrycks, Mantas Mazeika, and Thomas Dietterich · 2018
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Kimin Lee, Kibok Lee, Honglak Lee, and Jinwoo Shin · 2018
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Yusha Liu, Chun-Liang Li, and Barnabás Póczos · 2018
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Anomaly detection in nanofibrous materials by cnn-based self-similarity
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Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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Deep one-class classification
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Niv Cohen and Yedid Hoshen · 2020
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Anne-Sophie Collin and Christophe De Vleeschouwer · 2020
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Spotting defects! — deep metric learning solution for mvtec anomaly detection dataset
daisukelab · 2020
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Momentum contrast for unsupervised visual representation learning
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Why normalizing flows fail to detect out-of-distribution data
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Modeling the distribution of normal data in pre-trained deep features for anomaly detection
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Same same but differnet: Semi-supervised defect detection with normalizing flows
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A unifying review of deep and shallow anomaly detection
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Puzzle-ae: Novelty detection in images through solving puzzles
Mohammadreza Salehi, Ainaz Eftekhar, Niousha Sadjadi, Mohammad Hossein Rohban, and Hamid R Rabiee · 2020
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Csi: Novelty detection via contrastive learning on distributionally shifted instances
Jihoon Tack, Sangwoo Mo, Jongheon Jeong, and Jinwoo Shin · 2020
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Distance-based anomaly detection for industrial surfaces using triplet networks
Tareq Tayeh, Sulaiman Aburakhia, Ryan Myers, and Abdallah Shami · 2020
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Patch svdd: Patch-level svdd for anomaly detection and segmentation
Jihun Yi and Sungroh Yoon · 2020
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Random erasing data augmentation
Zhun Zhong, Liang Zheng, Guoliang Kang, Shaozi Li, and Yi Yang · 2020
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Learning and evaluating representations for deep one-class classification
Kihyuk Sohn, Chun-Liang Li, Jinsung Yoon, Minho Jin, and Tomas Pfister · 2021
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