{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T01:47:30Z","timestamp":1785548850725,"version":"3.56.0"},"reference-count":77,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"4","license":[{"start":{"date-parts":[[2018,4,1]],"date-time":"2018-04-01T00:00:00Z","timestamp":1522540800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"}],"funder":[{"name":"EU Framework Programme for Research and Innovation Horizon 2020","award":["645331"],"award-info":[{"award-number":["645331"]}]},{"name":"Swiss Commission for Technology and Innovation","award":["19015.1 PFES-ES"],"award-info":[{"award-number":["19015.1 PFES-ES"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Pattern Anal. Mach. Intell."],"published-print":{"date-parts":[[2018,4,1]]},"DOI":"10.1109\/tpami.2017.2700300","type":"journal-article","created":{"date-parts":[[2017,5,2]],"date-time":"2017-05-02T18:23:31Z","timestamp":1493749411000},"page":"819-833","source":"Crossref","is-referenced-by-count":175,"title":["Convolutional Oriented Boundaries: From Image Segmentation to High-Level Tasks"],"prefix":"10.1109","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3776-0049","authenticated-orcid":false,"given":"Kevis-Kokitsi","family":"Maninis","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7133-3724","authenticated-orcid":false,"given":"Jordi","family":"Pont-Tuset","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pablo","family":"Arbelaez","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luc","family":"Van Gool","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2465908"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.181"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.81"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.169"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.91"},{"key":"ref77","first-page":"379","article-title":"R-FCN: Object detection via region-based fully\n convolutional networks","author":"dai","year":"2016","journal-title":"Proc Conf Neural Inf Process Syst (NIPS)"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.579"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.79"},{"key":"ref75","first-page":"21","article-title":"SSD: Single shot multibox detector","author":"liu","year":"2016","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.28"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-017-1004-z"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.392"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2014.2377715"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.406"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.179"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.27"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298782"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-88690-7_40"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-013-0620-5"},{"key":"ref62","first-page":"336","article-title":"RIGOR:\n Recycling inference in graph cuts for generating object regions","author":"humayun","year":"2014","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.310"},{"key":"ref63","first-page":"91","article-title":"Faster R-CNN: Towards real-time object detection with\n region proposal networks","author":"ren","year":"2015","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-15552-9_47"},{"key":"ref64","first-page":"391","article-title":"Edge boxes: Locating object proposals from edges","author":"zitnick","year":"2014","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2006.298"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.414"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.28"},{"key":"ref29","first-page":"584","article-title":"Discriminatively trained sparse code gradients for contour detection","author":"ren","year":"2012","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref67","first-page":"2536","article-title":"Prime object proposals with randomized Prim's algorithm","author":"man\u00e9n","year":"2013","journal-title":"Proc IEEE Int Conf Comput Vis"},{"key":"ref68","article-title":"Multi-scale context aggregation by dilated convolutions","author":"yu","year":"2016","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.660"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.164"},{"key":"ref1","article-title":"Pushing the boundaries of boundary detection using deep learning","author":"kokkinos","year":"2016","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref20","article-title":"Machine perception of three-dimensional solids","author":"roberts","year":"1963"},{"key":"ref22","first-page":"15","article-title":"Object enhancement and extraction","volume":"10","author":"prewitt","year":"1970","journal-title":"Picture Processing and Psychopictories"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/0262-8856(83)90006-9"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.1986.4767851"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1098\/rspb.1980.0020"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2003.1159946"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2004.1273918"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/34.1000236"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46448-0_35"},{"key":"ref59","first-page":"725","article-title":"Geodesic object proposals","author":"kr\u00e4henb\u00fchl","year":"2014","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2011.231"},{"key":"ref57","first-page":"1574","article-title":"Learning to propose objects","author":"kr\u00e4henb\u00fchl","year":"2015","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.187"},{"key":"ref55","first-page":"1990","article-title":"Learning to\n segment object candidates","author":"pinheiro","year":"2015","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref54","first-page":"75","article-title":"Learning to refine object\n segments","author":"pinheiro","year":"2016","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref53","first-page":"746","article-title":"Indoor\n segmentation and support inference from RGBD images","author":"silberman","year":"2012","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7299103"},{"key":"ref10","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2015","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref40","first-page":"345","article-title":"Learning rich features from\n RGB-D images for object detection and segmentation","author":"gupta","year":"2014","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2001.937655"},{"key":"ref13","article-title":"The PASCAL visual object classes challenge 2012\n (VOC2012) results","author":"everingham","year":"0"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2011.6126343"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.119"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2010.161"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2537320"},{"key":"ref18","first-page":"740","article-title":"Microsoft COCO: Common objects in context","author":"lin","year":"0","journal-title":"Proc Eur Conf Comput Vis (ECCV)"},{"key":"ref19","first-page":"140","article-title":"Deep retinal image\n understanding","author":"maninis","year":"2016","journal-title":"Proc Int Conf Med Image Comput Comput -Assisted Intervention"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.65"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7299067"},{"key":"ref6","first-page":"536","article-title":"N$^{4}$\n-fields: Neural network nearest\n neighbor fields for image transforms","author":"ganin","year":"2014","journal-title":"Proc Asian Conf Comput Vis"},{"key":"ref5","first-page":"3982","article-title":"DeepContour: A deep convolutional feature learned by\n positive-sharing loss for contour detection","author":"shen","year":"2015","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"ref8","first-page":"1097","article-title":"ImageNet\n classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1023\/B:VISI.0000022288.19776.77"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1145\/2647868.2654889"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2481406"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.262"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.5244\/C.29.110"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10578-9_52"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/34.868688"},{"key":"ref44","first-page":"562","article-title":"Deeply-supervised nets","author":"lee","year":"0","journal-title":"Proc Artif Intell Statist (AISTATS)"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/34.546254"}],"container-title":["IEEE Transactions on Pattern Analysis and Machine Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/34\/8306529\/07917294.pdf?arnumber=7917294","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T16:22:52Z","timestamp":1642004572000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/7917294\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,4,1]]},"references-count":77,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.1109\/tpami.2017.2700300","relation":{},"ISSN":["0162-8828","2160-9292"],"issn-type":[{"value":"0162-8828","type":"print"},{"value":"2160-9292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,4,1]]}}}