{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T07:34:18Z","timestamp":1767598458557,"version":"3.37.3"},"reference-count":56,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,7,5]],"date-time":"2021-07-05T00:00:00Z","timestamp":1625443200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,7,5]],"date-time":"2021-07-05T00:00:00Z","timestamp":1625443200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,7,5]]},"DOI":"10.1109\/icme51207.2021.9428185","type":"proceedings-article","created":{"date-parts":[[2021,6,9]],"date-time":"2021-06-09T21:14:21Z","timestamp":1623273261000},"page":"1-6","source":"Crossref","is-referenced-by-count":8,"title":["Deepmix: Online Auto Data Augmentation for Robust Visual Object Tracking"],"prefix":"10.1109","author":[{"given":"Ziyi","family":"Cheng","sequence":"first","affiliation":[{"name":"Kyushu University,Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuhong","family":"Ren","sequence":"additional","affiliation":[{"name":"Tianjin University of Technology,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Felix","family":"Juefei-Xu","sequence":"additional","affiliation":[{"name":"Alibaba Group,USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wanli","family":"Xue","sequence":"additional","affiliation":[{"name":"Tianjin University of Technology,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qing","family":"Guo","sequence":"additional","affiliation":[{"name":"Nanyang Technological University,Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lei","family":"Ma","sequence":"additional","affiliation":[{"name":"University of Alberta,Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianjun","family":"Zhao","sequence":"additional","affiliation":[{"name":"Kyushu University,Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00612"},{"article-title":"mixup: Beyond empirical risk minimization","year":"2017","author":"zhang","key":"ref38"},{"article-title":"On calibration of modern neural networks","year":"2017","author":"guo","key":"ref33"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"ref31","first-page":"3642","article-title":"Multi-column deep neural networks for image classification","author":"ciregan","year":"2012","journal-title":"CVPR"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00411"},{"article-title":"Augmix: A simple data processing method to improve robustness and uncertainty","year":"2019","author":"hendrycks","key":"ref37"},{"key":"ref36","first-page":"6665","article-title":"Fast autoaugment","author":"lim","year":"2019","journal-title":"NeurIPS"},{"key":"ref35","first-page":"2731","article-title":"Population based augmentation: Efficient learning of augmentation policy schedules","author":"ho","year":"2019","journal-title":"ICML"},{"article-title":"Autoaugment: Learning augmentation policies from data","year":"2018","author":"cubuk","key":"ref34"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.159"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.733"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.196"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00441"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2020.3045630"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICME.2016.7552880"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00670"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00632"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00721"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00675"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58592-1_13"},{"key":"ref50","first-page":"630","article-title":"Identity mappings in deep residual networks","author":"he","year":"2016","journal-title":"ECCV"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"article-title":"Bias field poses a threat to dnn-based x-ray recognition","year":"2020","author":"tian","key":"ref56"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01043"},{"key":"ref54","article-title":"Efficientderain: Learning pixel-wise dilation filtering for high-efficiency single-image deraining","author":"guo","year":"2021","journal-title":"AAAI"},{"article-title":"It’s raining cats or dogs? adversarial rain attack on dnn perception","year":"2020","author":"zhai","key":"ref53"},{"key":"ref52","article-title":"Watch out! motion is blurring the vision of your deep neural networks","volume":"33","author":"guo","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2895411"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2955292"},{"key":"ref40","article-title":"Augmix: A simple method to improve robustness and uncertainty under data shift","author":"hendrycks","year":"2020","journal-title":"ICLRE"},{"key":"ref12","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-319-48881-3_56","article-title":"Fully-convolutional siamese networks for object tracking","author":"bertinetto","year":"2016"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00935"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00628"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01240-3_7"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00441"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2014.2388226"},{"key":"ref18","first-page":"0","article-title":"The sixth visual object tracking vot2018 challenge results","author":"kristan","year":"2018","journal-title":"ECCV"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00552"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00628"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58595-2_13"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2014.2345390"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2010.5539960"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2017.7952496"},{"key":"ref49","first-page":"1","article-title":"The visual object tracking vot2015 challenge results","author":"kristan","year":"2015","journal-title":"ICCV"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.490"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-97304-3_5"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00480"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00814"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00472"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00142"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00626"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00100"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.6899"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00479"}],"event":{"name":"2021 IEEE International Conference on Multimedia and Expo (ICME)","start":{"date-parts":[[2021,7,5]]},"location":"Shenzhen, China","end":{"date-parts":[[2021,7,9]]}},"container-title":["2021 IEEE International Conference on Multimedia and Expo (ICME)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9428049\/9428068\/09428185.pdf?arnumber=9428185","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,3]],"date-time":"2022-08-03T00:24:11Z","timestamp":1659486251000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9428185\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,5]]},"references-count":56,"URL":"https:\/\/doi.org\/10.1109\/icme51207.2021.9428185","relation":{},"subject":[],"published":{"date-parts":[[2021,7,5]]}}}