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Anomaly detection from a single image is challenging since anomaly data is always rare and can be with highly unpredictable types.
Gradient-based learning applied to document recognition
Yann LeCun, Léon Bottou, Yoshua Bengio, and Patrick Haffner · 1998
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Support vector data description
David MJ Tax and Robert PW Duin · 2004
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Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli · 2004
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Visualizing data using t-sne
Laurens van der Maaten and Geoffrey Hinton · 2008
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Learning multiple layers of features from tiny images
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
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Carl Doersch, Abhinav Gupta, and Alexei A Efros · 2015
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Going deeper with convolutions
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich · 2015
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Transfer representation-learning for anomaly detection
Jerone Andrews, Thomas Tanay, Edward J Morton, and Lewis D Griffin · 2016
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Defect detection in sem images of nanofibrous materials
Diego Carrera, Fabio Manganini, Giacomo Boracchi, and Ettore Lanzarone · 2016
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Infogan: Interpretable representation learning by information maximizing generative adversarial nets
Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever, and Pieter Abbeel · 2016
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Unsupervised learning of visual representations by solving jigsaw puzzles
Mehdi Noroozi and Paolo Favaro · 2016
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f-gan: Training generative neural samplers using variational divergence minimization
Sebastian Nowozin, Botond Cseke, and Ryota Tomioka · 2016
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Unsupervised representation learning with deep convolutional generative adversarial networks
Alec Radford, Luke Metz, and Soumith Chintala · 2016
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Colorful image colorization
Richard Zhang, Phillip Isola, and Alexei A Efros · 2016
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Martin Arjovsky, Soumith Chintala, and Léon Bottou · 2017
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Outlier detection
Zimek Arthur and Schubert Erich · 2017
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Arbitrary style transfer in real-time with adaptive instance normalization
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Mehdi Noroozi, Hamed Pirsiavash, and Paolo Favaro · 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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Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms
Han Xiao, Kashif Rasul, and Roland Vollgraf · 2017
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Amanda Berg, Jörgen Ahlberg, and Michael Felsberg · 2019
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Mvtec ad–a comprehensive real-world dataset for unsupervised anomaly detection
Paul Bergmann, Michael Fauser, David Sattlegger, and Carsten Steger · 2019
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Memorizing normality to detect anomaly: Memory-augmented deep autoencoder for unsupervised anomaly detection
Dong Gong, Lingqiao Liu, Vuong Le, Budhaditya Saha, Moussa Reda Mansour, Svetha Venkatesh, and Anton van den Hengel · 2019
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Clustergan: Latent space clustering in generative adversarial networks
Sudipto Mukherjee, Himanshu Asnani, Eugene Lin, and Sreeram Kannan · 2019
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Pathological evidence exploration in deep retinal image diagnosis
Yuhao Niu, Lin Gu, Feng Lu, Feifan Lv, Zongji Wang, Imari Sato, Zijian Zhang, Yangyan Xiao, Xunzhang Dai, and Tingting Cheng · 2019
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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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Deep autoencoding models for unsupervised anomaly segmentation in brain mr images
Christoph Baur, Benedikt Wiestler, Shadi Albarqouni, and Nassir Navab · 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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Image anomaly detection with generative adversarial networks
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Unsupervised representation learning by predicting image rotations
Spyros Gidaris, Praveer Singh, and Nikos Komodakis · 2018
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Multimodal unsupervised image-to-image translation
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Anomaly detection in nanofibrous materials by cnn-based self-similarity
Paolo Napoletano, Flavio Piccoli, and Raimondo Schettini · 2018
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Ocgan: One-class novelty detection using gans with constrained latent representations
Pramuditha Perera, Ramesh Nallapati, and Bing Xiang · 2019
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f-anogan: Fast unsupervised anomaly detection with generative adversarial networks
Thomas Schlegl, Philipp Seeböck, Sebastian M Waldstein, Georg Langs, and Ursula Schmidt-Erfurth · 2019
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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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Iterative energy-based projection on a normal data manifold for anomaly localization
David Dehaene, Oriel Frigo, Sébastien Combrexelle, and Pierre Eline · 2020
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Mutual mean-teaching: Pseudo label refinery for unsupervised domain adaptation on person re-identification
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Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
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Exploring deep anomaly detection methods based on capsule net
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Towards visually explaining variational autoencoders
Wenqian Liu, Runze Li, Meng Zheng, Srikrishna Karanam, Ziyan Wu, Bir Bhanu, Richard J Radke, and Octavia Camps · 2020
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Deep semi-supervised anomaly detection
Lukas Ruff, Robert A Vandermeulen, Nico Görnitz, Alexander Binder, Emmanuel Müller, Klaus-Robert Müller, and Marius Kloft · 2020
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On mutual information maximization for representation learning
Michael Tschannen, Josip Djolonga, Paul K Rubenstein, Sylvain Gelly, and Mario Lucic · 2020
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Attention guided anomaly detection and localization in images
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Encoding structure-texture relation with p-net for anomaly detection in retinal images
Kang Zhou, Yuting Xiao, Jianlong Yang, Jun Cheng, Wen Liu, Weixin Luo, Zaiwang Gu, Jiang Liu, and Shenghua. Gao · 2020
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