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This paper presents a novel evaluation framework for Out-of-Distribution (OOD) detection that aims to assess the performance of machine learning models in more realistic settings.
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Sparse reconstruction cost for abnormal event detection
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Generative adversarial nets
Ian J Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C Courville, and Yoshua Bengio · 2014
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Anomaly detection using autoencoders with nonlinear dimensionality reduction
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Learning deep representations of appearance and motion for anomalous event detection
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Video anomaly detection and localisation based on the sparsity and reconstruction error of auto-encoder
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Abnormal event detection in videos using spatiotemporal autoencoder
Yong Shean Chong and Yong Haur Tay · 2017
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Anomaly detection with robust deep autoencoders
Chong Zhou and Randy C Paffenroth · 2017
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Enhancing the reliability of out-of-distribution image detection in neural networks
Shiyu Liang, Yixuan Li, and Rayadurgam Srikant · 2018
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Mohammad Sabokrou, Mohammad Khalooei, Mahmood Fathy, and Ehsan Adeli · 2018
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Bo Zong, Qi Song, Martin Renqiang Min, Wei Cheng, Cristian Lumezanu, Daeki Cho, and Haifeng Chen · 2018
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Davide Abati, Angelo Porrello, Simone Calderara, and Rita Cucchiara · 2019
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Dan Hendrycks and Thomas G. Dietterich · 2019
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Jihoon Tack, Sangwoo Mo, Jongheon Jeong, and Jinwoo Shin · 2020
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Old is gold: Redefining the adversarially learned one-class classifier training paradigm
Muhammad Zaigham Zaheer, Jin-ha Lee, Marcella Astrid, and Seung-Ik Lee · 2020
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Panda: Adapting pretrained features for anomaly detection and segmentation
Tal Reiss, Niv Cohen, Liron Bergman, and Yedid Hoshen · 2021
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Mohammadreza Salehi, Hossein Mirzaei, Dan Hendrycks, Yixuan Li, Mohammad Hossein Rohban, and Mohammad Sabokrou · 2021
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Ssd: A unified framework for self-supervised outlier detection
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Using self-supervised learning can improve model robustness and uncertainty
Dan Hendrycks, Mantas Mazeika, Saurav Kadavath, and Dawn Song · 2019
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Pramuditha Perera, Ramesh Nallapati, and Bing Xiang · 2019
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Liron Bergman, Niv Cohen, and Yedid Hoshen · 2020
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Classification-based anomaly detection for general data
Liron Bergman and Yedid Hoshen · 2020
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Vikash Sehwag, Mung Chiang, and Prateek Mittal · 2021
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Generalized out-of-distribution detection: A survey
Jingkang Yang, Kaiyang Zhou, Yixuan Li, and Ziwei Liu · 2021
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One-class learned encoder-decoder network with adversarial context masking for novelty detection
John Taylor Jewell, Vahid Reza Khazaie, and Yalda Mohsenzadeh · 2022
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Generative cooperative learning for unsupervised video anomaly detection
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Fake it till you make it: Near-distribution novelty detection by score-based generative models
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