{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T01:31:44Z","timestamp":1772847104230,"version":"3.50.1"},"reference-count":100,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100004608","name":"Natural Science Foundation of Jiangsu Province","doi-asserted-by":"publisher","award":["BK20190019"],"award-info":[{"award-number":["BK20190019"]}],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62072244"],"award-info":[{"award-number":["62072244"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61972204"],"award-info":[{"award-number":["61972204"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["30921011104"],"award-info":[{"award-number":["30921011104"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Pattern Anal. Mach. Intell."],"published-print":{"date-parts":[[2023,1,1]]},"DOI":"10.1109\/tpami.2022.3147974","type":"journal-article","created":{"date-parts":[[2022,2,1]],"date-time":"2022-02-01T20:46:13Z","timestamp":1643748373000},"page":"1267-1286","source":"Crossref","is-referenced-by-count":5,"title":["Visual Micro-Pattern Propagation"],"prefix":"10.1109","volume":"45","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0543-4196","authenticated-orcid":false,"given":"Zhen","family":"Cui","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7227-783X","authenticated-orcid":false,"given":"Ling","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu, China"}]},{"given":"Chaoqun","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0814-4362","authenticated-orcid":false,"given":"Chunyan","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4800-832X","authenticated-orcid":false,"given":"Jian","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu, China"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00999"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00167"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2016.32"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00037"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.25"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00281"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.594"},{"key":"ref36","first-page":"2366","article-title":"Depth map prediction from a single image using a multi-scale deep network","author":"eigen","year":"2014","journal-title":"Proc 27th Int Conf Neural Inf Process Syst Found"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00578"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00214"},{"key":"ref28","first-page":"1161","article-title":"Learning depth from single monocular images","author":"saxena","year":"2006","journal-title":"Proc Neural Inf Process Syst Found"},{"key":"ref27","first-page":"4835","article-title":"Deep multimodal fusion by channel exchanging","author":"wang","year":"2020","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2008.132"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.539"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01252-6_9"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.533"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.304"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.202"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00194"},{"key":"ref100","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.345"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.556"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01249-6_15"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00146"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.312"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00935"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.733"},{"key":"ref56","first-page":"850","article-title":"Fully-convolutional siamese networks for object tracking","author":"bertinetto","year":"2016","journal-title":"In Proc European Conf Comp Vis"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2014.2345390"},{"key":"ref54","first-page":"254","article-title":"A scale adaptive kernel correlation filter tracker with feature integration","author":"li","year":"2014","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2019.2926728"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00423"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.421"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298897"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2644615"},{"key":"ref6","first-page":"91","article-title":"Faster R-CNN: Towards real-time object detection with region proposal networks","author":"ren","year":"2015","journal-title":"Proc 28th Int Conf Neural Inf Process Syst"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00393"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3240508.3240668"},{"key":"ref49","first-page":"3994","article-title":"Cross-stitch networks for multi-task learning","author":"ishan","year":"2016","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"ref7","first-page":"4293","article-title":"Learning multi-domain convolutional neural networks for visual tracking","author":"nam","year":"2016","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"ref9","author":"hyv\u00e4rinen","year":"2009","journal-title":"Natural Image Statistics A Probabilistic Approach to Early Computational Vision"},{"key":"ref46","first-page":"964","article-title":"A dirty model for multi-task learning","author":"ali","year":"2010","journal-title":"Proc 23rd Int Conf Neural Inf Process Syst Found"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00077"},{"key":"ref48","first-page":"1358","article-title":"Fine-grained recognition in the wild: A multi-task domain adaptation approach","author":"timnit","year":"2017","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"ref47","first-page":"3320","article-title":"How transferable are features in deep neural networks?","author":"jason","year":"2014","journal-title":"Proc 27th Int Conf Neural Inform Process Syst Found"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10602-1_31"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10599-4_44"},{"key":"ref44","first-page":"172","article-title":"SURGE: Surface regularized geometry estimation from a single image","author":"wang","year":"2016","journal-title":"Proc 30th Int Conf Neural Inf Process Syst Found"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298652"},{"key":"ref73","first-page":"4563","article-title":"Adaptive sampling towards fast graph representation learning","author":"huang","year":"2018","journal-title":"Proc 32nd Int Conf Adv Neural Inf Process Syst"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219947"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.11"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1109\/JSTSP.2017.2726981"},{"key":"ref76","first-page":"2014","article-title":"Learning convolutional neural networks for graphs","author":"niepert","year":"2016","journal-title":"Proc 33rd Int Conf Mach Learn"},{"key":"ref77","first-page":"1025","article-title":"Inductive representation learning on large graphs","author":"hamilton","year":"2017","journal-title":"Proc 31st Int Conf Adv Neural Inf Process Syst"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33014424"},{"key":"ref75","first-page":"2001","article-title":"Diffusion-convolutional neural networks","author":"atwood","year":"2016","journal-title":"Proc 30th Int Conf Adv Neural Inf Process Syst"},{"key":"ref78","article-title":"Graph attention networks","author":"velickovi?","year":"2017"},{"key":"ref79","first-page":"5449","article-title":"Representation learning on graphs with jumping knowledge networks","author":"xu","year":"2018","journal-title":"Proc 35th Int Conf Mach Learn"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2014.2388226"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00814"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01225-0_6"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1007\/s00138-013-0570-5"},{"key":"ref64","first-page":"1","article-title":"Multiple source data fusion via sparse representation for robust visual tracking","author":"wu","year":"2011","journal-title":"Proc 14th Int Conf Inf Fusion"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2018.10.002"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01261-8_49"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2017.11.068"},{"key":"ref68","article-title":"FANet: Quality-aware feature aggregation network for robust RGB-T tracking","author":"zhu","year":"2018"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2016.69"},{"key":"ref69","first-page":"1263","article-title":"Neural message passing for quantum chemistry","author":"gilmer","year":"2017","journal-title":"Proc 34th Int Conf Mach Learn"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.549"},{"key":"ref95","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2019.00279"},{"key":"ref94","first-page":"472","article-title":"Beyond correlation filters: Learning continuous convolution operators for visual tracking","author":"danelljan","year":"2016","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref93","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.642"},{"key":"ref92","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00996"},{"key":"ref91","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00412"},{"key":"ref90","first-page":"1119","article-title":"Depth and surface normal estimation from monocular images using regression on deep features and hierarchical CRFs","author":"li","year":"2015","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"ref98","first-page":"725","article-title":"Weighted low-rank decomposition for robust grayscale-thermal foreground detection","volume":"27","author":"li","year":"2017","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"key":"ref99","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2509974"},{"key":"ref96","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2019.00017"},{"key":"ref97","doi-asserted-by":"publisher","DOI":"10.3390\/s20020393"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2011.5995401"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2019.106977"},{"key":"ref12","first-page":"746","article-title":"Indoor segmentation and support inference from RGBD images","author":"nathan","year":"2012","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00457"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00709"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298655"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2016.2614135"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5861"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00383"},{"key":"ref81","article-title":"Anonymous walk embeddings","author":"ivanov","year":"2018"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref84","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2699184"},{"key":"ref83","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58520-4_3"},{"key":"ref80","first-page":"1853","article-title":"Symbolic graph reasoning meets convolutions","volume":"31","author":"liang","year":"2018","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref89","article-title":"Bayesian SegNet: Model uncertainty in deep convolutional encoder-decoder architectures for scene understanding","author":"kendall","year":"2015"},{"key":"ref85","doi-asserted-by":"publisher","DOI":"10.5244\/C.28.6"},{"key":"ref86","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3350928"},{"key":"ref87","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.161"},{"key":"ref88","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.348"}],"container-title":["IEEE Transactions on Pattern Analysis and Machine Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/34\/9970415\/09699065.pdf?arnumber=9699065","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,26]],"date-time":"2022-12-26T19:13:42Z","timestamp":1672082022000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9699065\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,1]]},"references-count":100,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tpami.2022.3147974","relation":{},"ISSN":["0162-8828","2160-9292","1939-3539"],"issn-type":[{"value":"0162-8828","type":"print"},{"value":"2160-9292","type":"electronic"},{"value":"1939-3539","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,1,1]]}}}