{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,29]],"date-time":"2024-10-29T11:04:26Z","timestamp":1730199866552,"version":"3.28.0"},"reference-count":43,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,11,16]],"date-time":"2021-11-16T00:00:00Z","timestamp":1637020800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,11,16]],"date-time":"2021-11-16T00:00:00Z","timestamp":1637020800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,11,16]],"date-time":"2021-11-16T00:00:00Z","timestamp":1637020800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,11,16]]},"DOI":"10.1109\/avss52988.2021.9663783","type":"proceedings-article","created":{"date-parts":[[2022,1,5]],"date-time":"2022-01-05T20:43:05Z","timestamp":1641415385000},"page":"1-8","source":"Crossref","is-referenced-by-count":4,"title":["Fine-grained anomaly detection via multi-task self-supervision"],"prefix":"10.1109","author":[{"given":"Loic","family":"Jezequel","sequence":"first","affiliation":[]},{"given":"Ngoc-Son","family":"Vu","sequence":"additional","affiliation":[]},{"given":"Jean","family":"Beaudet","sequence":"additional","affiliation":[]},{"given":"Aymeric","family":"Histace","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","article-title":"Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms","volume":"abs 1708 7747","author":"xiao","year":"2017","journal-title":"CoRR"},{"journal-title":"Caltech-UCSD Birds 200","year":"2010","author":"welinder","key":"ref38"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00678"},{"key":"ref32","first-page":"1929","article-title":"Dropout: a simple way to prevent neural networks from overfitting","volume":"15","author":"srivastava","year":"2014","journal-title":"J Mach Learn Res"},{"key":"ref31","first-page":"582","article-title":"Support vector method for novelty detection","author":"sch\u00f6lkopf","year":"1999","journal-title":"Proceedings of the 12th International Conference on Neural Information Processing Systems"},{"key":"ref30","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1007\/978-3-319-59050-9_12","article-title":"Unsupervised anomaly detection with generative adversarial networks to guide marker discovery","author":"schlegl","year":"2017","journal-title":"International Conference on Information Processing in Medical Imaging"},{"key":"ref37","first-page":"4790","article-title":"Conditional image generation with pixel-cnn decoders","author":"van den oord","year":"2016","journal-title":"Advances in neural information processing systems"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-41404-7_12"},{"key":"ref35","article-title":"CSI: novelty detection via contrastive learning on distributionally shifted instances","author":"tack","year":"2020","journal-title":"Advances in Neural Information Processing Systems 33 Annual Conference on Neural Information Processing Systems 2020 NeurIPS 2020 virtual"},{"key":"ref34","first-page":"1139","article-title":"On the importance of initialization and momentum in deep learning","author":"sutskever","year":"2013","journal-title":"Proceedings of the 30th International Conference on Machine Learning volume 28 of Proceedings of Machine Learning Research"},{"key":"ref10","first-page":"9758","article-title":"Deep anomaly detection using geometric transformations","volume":"31","author":"golan","year":"2018","journal-title":"Advances in neural information processing systems"},{"key":"ref40","doi-asserted-by":"crossref","DOI":"10.5244\/C.30.87","article-title":"Wide residual networks","author":"zagoruyko","year":"2016","journal-title":"Proceedings of the British Machine Vision Conference 2016 BMVC 2016"},{"key":"ref11","article-title":"Drocc: Deep robust one-class classification","author":"goyal","year":"2020","journal-title":"International Conference on Machine Learning"},{"key":"ref12","article-title":"Using self-supervised learning can improve model robustness and uncertainty","author":"hendrycks","year":"2019","journal-title":"Advances in Neural IInformation Processing Systems"},{"key":"ref13","article-title":"Auto-encoding variational bayes","author":"kingma","year":"2014","journal-title":"Conference proceedings papers accepted to the International Conference on Learning Representations (ICLR)"},{"article-title":"Learning multiple layers of features from tiny images","year":"2009","author":"krizhevsky","key":"ref14"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/s10586-017-1117-8"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref17","first-page":"413","article-title":"Isolation forest","author":"liu","year":"2009","journal-title":"2008 Eighth IEEE International Conference on Data Mining"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.439"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00481"},{"key":"ref28","first-page":"4393","article-title":"Deep one-class classification","volume":"80","author":"ruff","year":"2018","journal-title":"Proceedings of the 35th International Conference on Machine Learning"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-10925-7_1"},{"key":"ref27","article-title":"Deep semi-supervised anomaly detection","author":"ruff","year":"2020","journal-title":"International Conference on Learning Representations"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1023\/A:1007379606734","article-title":"Multitask learning","volume":"28","author":"caruana","year":"1997","journal-title":"Machine Learning"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.167"},{"key":"ref29","article-title":"Puzzle-ae: Novelty detection in images through solving puzzles","volume":"abs 2008 12959","author":"salehi","year":"0"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-45014-9_1"},{"key":"ref8","first-page":"1","article-title":"Attribute Restoration Framework for Anomaly Detection","author":"fei","year":"2020","journal-title":"IEEE Transactions on Multimedia"},{"key":"ref7","first-page":"1","article-title":"Discriminative unsupervised feature learning with exemplar convolutional neural networks","author":"dosovitskiy","year":"2014","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"ref2","article-title":"A critical analysis of self-supervision, or what we can learn from a single image","author":"asano","year":"2020","journal-title":"International Conference on Learning Representations"},{"key":"ref1","first-page":"622","article-title":"Ganomaly: Semi-supervised anomaly detection via adversarial training","author":"akcay","year":"2018","journal-title":"Asian Conference on Computer Vision"},{"key":"ref9","article-title":"Unsupervised representation learning by predicting image rotations","author":"gidaris","year":"2018","journal-title":"6th International Conference on Learning Representations ICLR 2018"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.zemedi.2018.11.002"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46466-4_5"},{"key":"ref21","article-title":"Reading digits in natural images with unsupervised feature learning","author":"netzer","year":"2011","journal-title":"NIPS Workshop on Deep Learning and Unsupervised Feature Learning"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.278"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/5680264"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330871"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46487-9_40"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00301"},{"key":"ref25","article-title":"Detection of adversarial training examples in poisoning attacks through anomaly detection","volume":"abs 1802 3041","author":"paudice","year":"2018","journal-title":"CoRR"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-03243-2_845-1"}],"event":{"name":"2021 17th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)","start":{"date-parts":[[2021,11,16]]},"location":"Washington, DC, USA","end":{"date-parts":[[2021,11,19]]}},"container-title":["2021 17th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9663572\/9663735\/09663783.pdf?arnumber=9663783","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T16:56:51Z","timestamp":1652201811000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9663783\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,16]]},"references-count":43,"URL":"https:\/\/doi.org\/10.1109\/avss52988.2021.9663783","relation":{},"subject":[],"published":{"date-parts":[[2021,11,16]]}}}