{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T17:01:16Z","timestamp":1775667676473,"version":"3.50.1"},"reference-count":46,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,3,1]],"date-time":"2020-03-01T00:00:00Z","timestamp":1583020800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,3,1]],"date-time":"2020-03-01T00:00:00Z","timestamp":1583020800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,3,1]],"date-time":"2020-03-01T00:00:00Z","timestamp":1583020800000},"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":[[2020,3]]},"DOI":"10.1109\/wacv45572.2020.9093590","type":"proceedings-article","created":{"date-parts":[[2020,5,15]],"date-time":"2020-05-15T03:41:09Z","timestamp":1589514069000},"page":"2694-2702","source":"Crossref","is-referenced-by-count":27,"title":["Devon: Deformable Volume Network for Learning Optical Flow"],"prefix":"10.1109","author":[{"given":"Yao","family":"Lu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jack","family":"Valmadre","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Heng","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Juho","family":"Kannala","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mehrtash","family":"Harandi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Philip H. S.","family":"Torr","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.5244\/C.30.145"},{"key":"ref38","article-title":"Learning to extract motion from videos in convolutional neural networks","author":"teney","year":"2016","journal-title":"ArXiv"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref32","doi-asserted-by":"crossref","DOI":"10.1609\/aaai.v31i1.10723","article-title":"Un-supervised deep learning for optical flow estimation","author":"ren","year":"2017","journal-title":"AAAI"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.291"},{"key":"ref30","article-title":"Continual occlusion and optical flow estimation","author":"neoral","year":"2018","journal-title":"ACCV"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00931"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10590-1_28"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1023\/A:1014573219977"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-006-0016-x"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2012.6248074"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.596"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1023\/A:1008112528134"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(81)90024-2"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00936"},{"key":"ref16","article-title":"Generalized de-formable spatial pyramid: Geometry-preserving dense correspondence estimation","author":"hur","year":"2015","journal-title":"CVPR"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00590"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.179"},{"key":"ref19","article-title":"Occlusions, motion and depth boundaries with a generic network for disparity, optical flow or scene flow estimation","author":"ilg","year":"2018","journal-title":"ECCV"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.438"},{"key":"ref4","article-title":"A naturalistic open source movie for optical flow evaluation","author":"butler","year":"2012","journal-title":"ECCV"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-018-1082-6"},{"key":"ref3","article-title":"High accuracy optical flow estimation based on a theory for warping","author":"brox","year":"2004","journal-title":"ECCV"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.89"},{"key":"ref29","doi-asserted-by":"crossref","DOI":"10.1609\/aaai.v32i1.12276","article-title":"Unflow: Unsupervised learning of optical flow with a bidirectional census loss","author":"meister","year":"2018","journal-title":"AAAI"},{"key":"ref5","article-title":"Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs","author":"chen","year":"2016","journal-title":"ArXiv"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/0-387-28831-7_15"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.316"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206697"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2015.02.008"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/212094.212141"},{"key":"ref46","article-title":"Stereo matching by training a convolutional neural network to compare image patches","author":"zbontar","year":"2016","journal-title":"JMLR"},{"key":"ref20","article-title":"Spatial transformer networks","author":"jaderberg","year":"2015","journal-title":"NIPS"},{"key":"ref45","article-title":"Multi-scale context aggregation by dilated convolutions","author":"yu","year":"2015","journal-title":"ICLRE"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.299"},{"key":"ref21","article-title":"Un-supervised learning of multi-frame optical flow with occlusions","author":"janai","year":"2018","journal-title":"ECCV"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00513"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00470"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2011.5995407"},{"key":"ref23","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014","journal-title":"ICLRE"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.401"},{"key":"ref26","article-title":"An iterative image registration technique with an application to stereo vision","author":"lucas","year":"1981","journal-title":"IJCAI"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.615"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2019.8852344"}],"event":{"name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","location":"Snowmass Village, CO, USA","start":{"date-parts":[[2020,3,1]]},"end":{"date-parts":[[2020,3,5]]}},"container-title":["2020 IEEE Winter Conference on Applications of Computer Vision (WACV)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9087828\/9093261\/09093590.pdf?arnumber=9093590","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,23]],"date-time":"2022-10-23T19:45:34Z","timestamp":1666554334000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9093590\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3]]},"references-count":46,"URL":"https:\/\/doi.org\/10.1109\/wacv45572.2020.9093590","relation":{},"subject":[],"published":{"date-parts":[[2020,3]]}}}