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Anomaly detection (AD) is a fundamental research problem in machine learning and computer vision, with practical applications in industrial inspection, video surveillance, and medical diagnosis.
Estimating the support of a high-dimensional distribution
Bernhard Schölkopf, John C Platt, John Shawe-Taylor, Alex J Smola, and Robert C Williamson · 2001
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Support vector data description
David MJ Tax and Robert PW Duin · 2004
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The multimodal brain tumor image segmentation benchmark (brats)
Bjoern H Menze, Andras Jakab, Stefan Bauer, Jayashree Kalpathy-Cramer, Keyvan Farahani, Justin Kirby, Yuliya Burren, Nicole Porz, Johannes Slotboom, Roland Wiest, et al · 2014
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Anomaly detection using autoencoders with nonlinear dimensionality reduction
Mayu Sakurada and Takehisa Yairi · 2014
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Miccai multi-atlas labeling beyond the cranial vault–workshop and challenge
Bennett Landman, Zhoubing Xu, J Igelsias, Martin Styner, T Langerak, and Arno Klein · 2015
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Variational inference with normalizing flows
Danilo Rezende and Shakir Mohamed · 2015
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Advancing the cancer genome atlas glioma mri collections with expert segmentation labels and radiomic features
Spyridon Bakas, Hamed Akbari, Aristeidis Sotiras, Michel Bilello, Martin Rozycki, Justin S Kirby, John B Freymann, Keyvan Farahani, and Christos Davatzikos · 2017
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Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer
Babak Ehteshami Bejnordi, Mitko Veta, Paul Johannes Van Diest, Bram Van Ginneken, Nico Karssemeijer, Geert Litjens, Jeroen AWM Van Der Laak, Meyke Hermsen, Quirine F Manson, Maschenka Balkenhol, et al · 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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Chestx-ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases
Xiaosong Wang, Yifan Peng, Le Lu, Zhiyong Lu, Mohammadhadi Bagheri, and Ronald M Summers · 2017
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Anomaly detection with robust deep autoencoders
Chong Zhou and Randy C Paffenroth · 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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Unsupervised detection of lesions in brain mri using constrained adversarial auto-encoders
Xiaoran Chen and Ender Konukoglu · 2018
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Identifying medical diagnoses and treatable diseases by image-based deep learning
Daniel S Kermany, Michael Goldbaum, Wenjia Cai, Carolina CS Valentim, Huiying Liang, Sally L Baxter, Alex McKeown, Ge Yang, Xiaokang Wu, Fangbing Yan, et al · 2018
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Cancer metastasis detection with neural conditional random field
Yi Li and Wei Ping · 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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Adversarially learned one-class classifier for novelty detection
Mohammad Sabokrou, Mohammad Khalooei, Mahmood Fathy, and Ehsan Adeli · 2018
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Fusing unsupervised and supervised deep learning for white matter lesion segmentation
Christoph Baur, Benedikt Wiestler, Shadi Albarqouni, and Nassir Navab · 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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The liver tumor segmentation benchmark (lits)
Patrick Bilic, Patrick Ferdinand Christ, Eugene Vorontsov, Grzegorz Chlebus, Hao Chen, Qi Dou, Chi-Wing Fu, Xiao Han, Pheng-Ann Heng, Jürgen Hesser, et al · 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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Automated segmentation of macular edema in oct using deep neural networks
Junjie Hu, Yuanyuan Chen, and Zhang Yi · 2019
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Discriminative pattern mining for breast cancer histopathology image classification via fully convolutional autoencoder
Xingyu Li, Marko Radulovic, Kenija Kanjer, and Konstanitinos N. Plataniotis · 2019
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Ocgan: One-class novelty detection using gans with constrained latent representations
Pramuditha Perera, Ramesh Nallapati, and Bing Xiang · 2019
Cited alongside, same era.
f-anogan: Fast unsupervised anomaly detection with generative adversarial networks
Thomas Schlegl, Philipp Seeböck, Sebastian M Waldstein, Georg Langs, and Ursula Schmidt-Erfurth · 2019
Cited alongside, same era.
Computer-aided detection of squamous carcinoma of the cervix in whole slide images
Ye Tian, Li Yang, Wei Wang, Jing Zhang, Qing Tang, Mili Ji, Yang Yu, Yu Li, Hong Yang, and Airong Qian · 2019
Cited alongside, same era.
Uninformed students: Student-teacher anomaly detection with discriminative latent embeddings
Paul Bergmann, Michael Fauser, David Sattlegger, and Carsten Steger · 2020
Cited alongside, same era.
Superpixel masking and inpainting for self-supervised anomaly detection
Zhenyu Li, Ning Li, Kaitao Jiang, Zhiheng Ma, Xing Wei, Xiaopeng Hong, and Yihong Gong · 2020
Cited alongside, same era.
Informative knowledge distillation for image anomaly segmentation
Yunkang Cao, Qian Wan, Weiming Shen, and Liang Gao · 2022
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Utrad: Anomaly detection and localization with u-transformer
Liyang Chen, Zhiyuan You, Nian Zhang, Juntong Xi, and Xinyi Le · 2022
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Cflow-ad: Real-time unsupervised anomaly detection with localization via conditional normalizing flows
Denis Gudovskiy, Shun Ishizaka, and Kazuki Kozuka · 2022
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Adbench: Anomaly detection benchmark
Songqiao Han, Xiyang Hu, Hailiang Huang, Minqi Jiang, and Yue Zhao · 2022
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Denoising autoencoders for unsupervised anomaly detection in brain mri
Antanas Kascenas, Nicolas Pugeault, and Alison Q O’Neil · 2022
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Cfa: Coupled-hypersphere-based feature adaptation for target-oriented anomaly localization
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Learning memory-guided normality for anomaly detection
Hyunjong Park, Jongyoun Noh, and Bumsub Ham · 2020
Cited alongside, same era.
Patch svdd: Patch-level svdd for anomaly detection and segmentation
Jihun Yi and Sungroh Yoon · 2020
Cited alongside, same era.
Viral pneumonia screening on chest x-rays using confidence-aware anomaly detection
Jianpeng Zhang, Yutong Xie, Guansong Pang, Zhibin Liao, Johan Verjans, Wenxing Li, Zongji Sun, Jian He, Yi Li, Chunhua Shen, et al · 2020
Cited alongside, same era.
Sparse-gan: Sparsity-constrained generative adversarial network for anomaly detection in retinal oct image
Kang Zhou, Shenghua Gao, Jun Cheng, Zaiwang Gu, Huazhu Fu, Zhi Tu, Jianlong Yang, Yitian Zhao, and Jiang Liu · 2020
Cited alongside, same era.
Ujjwal Baid, Satyam Ghodasara, Suyash Mohan, Michel Bilello, Evan Calabrese, Errol Colak, Keyvan Farahani, Jayashree Kalpathy-Cramer, Felipe C Kitamura, Sarthak Pati, et al · 2021
Cited alongside, same era.
Padim: a patch distribution modeling framework for anomaly detection and localization
Thomas Defard, Aleksandr Setkov, Angelique Loesch, and Romaric Audigier · 2021
Cited alongside, same era.
Asc-net: Adversarial-based selective network for unsupervised anomaly segmentation
Yi Dey, Raunak andAn Accurate Unsupervised Liver Hong · 2021
Cited alongside, same era.
Sungwook Lee, Seunghyun Lee, and Byung Cheol Song · 2022
Later among the works it cites.
Anovit: Unsupervised anomaly detection and localization with vision transformer-based encoder-decoder
Yunseung Lee and Pilsung Kang · 2022
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An accurate unsupervised liver lesion detection method using pseudo-lesions
He Li, Yutaro Iwamoto, Xianhua Han, Lanfen Lin, Hongjie Hu, and Yen-Wei Chen · 2022
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Towards total recall in industrial anomaly detection
Karsten Roth, Latha Pemula, Joaquin Zepeda, Bernhard Schölkopf, Thomas Brox, and Peter Gehler · 2022
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Fully convolutional cross-scale-flows for image-based defect detection
Marco Rudolph, Tom Wehrbein, Bodo Rosenhahn, and Bastian Wandt · 2022
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Detecting outliers with foreign patch interpolation
Jeremy Tan, Benjamin Hou, James Battern, Huaqi Qiu, and Bernhard Kainz · 2022
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Unsupervised visual defect detection with score-based generative model
Yapeng Teng, Haoyang Li, Fuzhen Cai, Ming Shao, and Siyu Xia · 2022
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Diffusion models for medical anomaly detection
Julia Wolleb, Florentin Bieder, Robin Sandkühler, and Philippe C Cattin · 2022
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Anoddpm: Anomaly detection with denoising diffusion probabilistic models using simplex noise
Julian Wyatt, Adam Leach, Sebastian M. Schmon, and Chris G. Willcocks · 2022
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Openood: Benchmarking generalized out-of-distribution detection
Jingkang Yang, Pengyun Wang, Dejian Zou, Zitang Zhou, Kunyuan Ding, Wenxuan Peng, Haoqi Wang, Guangyao Chen, Bo Li, Yiyou Sun, Xuefeng Du, Kaiyang Zhou, Wayne Zhang, Dan Hendrycks, Yixuan Li, and Ziwei Liu · 2022
Later among the works it cites.
Benchmarking unsupervised anomaly detection and localization
Ye Zheng, Xiang Wang, Yu Qi, Wei Li, and Liwei Wu · 2022
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The liver tumor segmentation benchmark (lits)
Patrick Bilic, Patrick Christ, Hongwei Bran Li, Eugene Vorontsov, Avi Ben-Cohen, Georgios Kaissis, Adi Szeskin, Colin Jacobs, Gabriel Efrain Humpire Mamani, Gabriel Chartrand, et al · 2023
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Whole-slide-imaging cancer metastases detection and localization with limited tumorous data
Yinsheng He and Xingyu Li · 2023
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Incremental self-supervised learning based on transformer for anomaly detection and localization
Wenping Jin, Fei Guo, and Li Zhu · 2023
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Simplenet: A simple network for image anomaly detection and localization
Zhikang Liu, Yiming Zhou, Yuansheng Xu, and Zilei Wang · 2023
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Asymmetric student-teacher networks for industrial anomaly detection
Marco Rudolph, Tom Wehrbein, Bodo Rosenhahn, and Bastian Wandt · 2023
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Revisiting reverse distillation for anomaly detection
Tran Dinh Tien, Anh Tuan Nguyen, Nguyen Hoang Tran, Ta Duc Huy, Soan T.M. Duong, Chanh D. Tr. Nguyen, and Steven Q. H. Truong · 2023
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Im-iad: Industrial image anomaly detection benchmark in manufacturing
Guoyang Xie, Jinbao Wang, Jiaqi Liu, Jiayi Lyu, Yong Liu, Chengjie Wang, Feng Zheng, and Yaochu Jin · 2023
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Adtr: Anomaly detection transformer with feature reconstruction
Zhiyuan You, Kai Yang, Wenhan Luo, Lei Cui, Yu Zheng, and Xinyi Le · 2023
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