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We introduce a powerful student-teacher framework for the challenging problem of unsupervised anomaly detection and pixel-precise anomaly segmentation in high-resolution images.
Modern multidimensional scaling: Theory and applications
Ingwer Borg and Patrick Groenen · 2003
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Dimensionality reduction by learning an invariant mapping
Raia Hadsell, Sumit Chopra, and Yann LeCun · 2006
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Learning multiple layers of features from tiny images
Alex Krizhevsky and Geoffrey Hinton · 2009
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MNIST handwritten digit database
Yann LeCun and Corinna Cortes · 2010
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ImageNet Classification With Deep Convolutional Neural Networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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A review of novelty detection
Marco AF Pimentel, David A Clifton, Lei Clifton, and Lionel Tarassenko · 2014
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Variational Autoencoder based Anomaly Detection using Reconstruction Probability
Jinwon An and Sungzoon Cho · 2015
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Adam: A Method for Stochastic Optimization
Diederik P Kingma and Jimmy Ba · 2015
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Transfer Representation-Learning for Anomaly Detection
Jerone TA Andrews, Thomas Tanay, Edward J Morton, and Lewis D Griffin · 2016
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Learning local feature descriptors with triplets and shallow convolutional neural networks
Daniel Ponsa Vassileios Balntas, Edgar Riba and Krystian Mikolajczyk · 2016
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Fast Dense Feature Extraction with CNNs that have Pooling or Striding Layers
Christian Bailer, Tewodros A Habtegebrial, Kiran Varanasi, and Didier Stricker · 2017
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What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?
Alex Kendall and Yarin Gal · 2017
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Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan, Alexander Pritzel, and Charles Blundell · 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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L2-Net: Deep Learning of Discriminative Patch Descriptor in Euclidean Space
Yurun Tian, Bin Fan, and Fuchao Wu · 2017
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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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The power of ensembles for active learning in image classification
William H. Beluch, Tim Genewein, Andreas Nürnberger, and Jan M. Köhler · 2018
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Latent space autoregression for novelty detection
D. Abati, A. Porrello, S. Calderara, and R. Cucchiara · 2019
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Where’s Wally Now? Deep Generative and Discriminative Embeddings for Novelty Detection
Philippe Burlina, Neil Joshi, and I-Jeng Wang · 2019
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Unsupervised natural image patch learning
Dov Danon, Hadar Averbuch-Elor, Ohad Fried, and Daniel Cohen-Or · 2019
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Do better imagenet models transfer better?
Simon Kornblith, Jonathon Shlens, and Quoc V. Le · 2019
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Deep transfer learning for multiple class novelty detection
Pramuditha Perera and Vishal M. Patel · 2019
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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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Raghavendra Chalapathy, Aditya Krishna Menon, and Sanjay Chawla · 2018
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Metric Learning for Novelty and Anomaly Detection
Marc Masana, Idoia Ruiz, Joan Serrat, Joost van de Weijer, and Antonio M Lopez · 2018
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Do Deep Generative Models Know What They Don’t Know?
Eric Nalisnick, Akihiro Matsukawa, Yee Whye Teh, Dilan Gorur, and Balaji Lakshminarayanan · 2018
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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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Are pre-trained cnns good feature extractors for anomaly detection in surveillance videos?
Tiago S Nazare, Rodrigo F de Mello, and Moacir A Ponti · 2018
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Deep one-class classification
Lukas Ruff, Robert Vandermeulen, Nico Goernitz, Lucas Deecke, Shoaib Ahmed Siddiqui, Alexander Binder, Emmanuel Müller, and Marius Kloft · 2018
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Deep-anomaly: Fully convolutional neural network for fast anomaly detection in crowded scenes
Mohammad Sabokrou, Mohsen Fayyaz, Mahmood Fathy, Zahra Moayed, and Reinhard Klette · 2018
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Informed democracy: Voting-based novelty detection for action recognition
Alina Roitberg, Ziad Al-Halah, and Rainer Stiefelhagen · 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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Exploiting Epistemic Uncertainty of Anatomy Segmentation for Anomaly Detection in Retinal OCT
Philipp Seebock, José Ignacio Orlando, Thomas Schlegl, Sebastian M Waldstein, Hrvoje Bogunovic, Sophie Klimscha, Georg Langs, and Ursula Schmidt-Erfurth · 2019
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Not all areas are equal: Transfer learning for semantic segmentation via hierarchical region selection
Ruoqi Sun, Xinge Zhu, Chongruo Wu, Chen Huang, Jianping Shi, and Lizhuang Ma · 2019
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q-Space Novelty Detection with Variational Autoencoders
A. Vasilev, V. Golkov, M. Meissner, I. Lipp, E. Sgarlata, V. Tomassini, D.K. Jones, and D. Cremers · 2019
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