{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T00:26:44Z","timestamp":1769732804540,"version":"3.49.0"},"reference-count":42,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,7,18]],"date-time":"2021-07-18T00:00:00Z","timestamp":1626566400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,7,18]],"date-time":"2021-07-18T00:00:00Z","timestamp":1626566400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,7,18]],"date-time":"2021-07-18T00:00:00Z","timestamp":1626566400000},"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":[[2021,7,18]]},"DOI":"10.1109\/ijcnn52387.2021.9533398","type":"proceedings-article","created":{"date-parts":[[2021,9,20]],"date-time":"2021-09-20T21:27:41Z","timestamp":1632173261000},"page":"1-8","source":"Crossref","is-referenced-by-count":2,"title":["NPLP: A Noisy Pseudo-Label Processing Approach for Unsupervised Domain-Adaptive Person Re-ID"],"prefix":"10.1109","author":[{"given":"Tianbao","family":"Liang","sequence":"first","affiliation":[]},{"given":"Jianming","family":"Lv","sequence":"additional","affiliation":[]},{"given":"Hualiang","family":"Li","sequence":"additional","affiliation":[]},{"given":"Yuzhong","family":"Liu","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298832"},{"key":"ref38","article-title":"Random erasing data augmentation","author":"zhong","year":"2017","journal-title":"ArXiv Preprint"},{"key":"ref33","article-title":"Rectified linear units improve restricted boltzmann machines","author":"nair","year":"2010","journal-title":"ICML"},{"key":"ref32","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"ioffe","year":"2015","journal-title":"ICML"},{"key":"ref31","article-title":"In defense of the triplet loss for person re-identification","author":"hermans","year":"2017","journal-title":"ArXiv Preprint"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00016"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.405"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-48881-3_2"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.133"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00541"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00242"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01261-8_11"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00069"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00829"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00375"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2019.107173"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00831"},{"key":"ref17","article-title":"A density-based algorithm for discovering clusters in large spatial databases with noise","author":"ester","year":"1996","journal-title":"KDD"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.240"},{"key":"ref19","article-title":"Toward robustness against label noise in training deep discriminative neural networks","author":"vahdat","year":"2017","journal-title":"NIPS"},{"key":"ref28","article-title":"Eanet: Enhancing alignment for cross-domain person reidentification","author":"huang","year":"2018","journal-title":"CoRR"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33018738"},{"key":"ref27","article-title":"Mutual mean-teaching: Pseudo label refinery for unsupervised domain adaptation on person re- identification","author":"ge","year":"2020","journal-title":"ICLRE"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3240508.3240552"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00242"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.266"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00110"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3243316"},{"key":"ref2","article-title":"Pyramidal person reidentification via multi -loss dynamic training","author":"zheng","year":"2019","journal-title":"CVPR"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00621"},{"key":"ref1","article-title":"Beyond part models: Person retrieval with refined part pooling (and A strong convolutional baseline)","author":"sun","year":"2018","journal-title":"ECCV"},{"key":"ref20","doi-asserted-by":"crossref","DOI":"10.1609\/aaai.v31i1.10894","article-title":"Robust loss functions under label noise for deep neural networks","author":"ghosh","year":"2017","journal-title":"AAAI"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"key":"ref21","article-title":"Generalized cross entropy loss for training deep neural networks with noisy labels","author":"zhang","year":"2018","journal-title":"NIPS"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00904"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00342"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01099"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00571"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00064"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00019"}],"event":{"name":"2021 International Joint Conference on Neural Networks (IJCNN)","location":"Shenzhen, China","start":{"date-parts":[[2021,7,18]]},"end":{"date-parts":[[2021,7,22]]}},"container-title":["2021 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9533266\/9533267\/09533398.pdf?arnumber=9533398","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,9]],"date-time":"2023-01-09T19:42:38Z","timestamp":1673293358000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9533398\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,18]]},"references-count":42,"URL":"https:\/\/doi.org\/10.1109\/ijcnn52387.2021.9533398","relation":{},"subject":[],"published":{"date-parts":[[2021,7,18]]}}}