{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T10:27:26Z","timestamp":1760956046869,"version":"3.37.3"},"reference-count":62,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Basic Research Program of China","doi-asserted-by":"publisher","award":["2020AAA0130200"],"award-info":[{"award-number":["2020AAA0130200"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61876177"],"award-info":[{"award-number":["61876177"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004826","name":"Beijing Natural Science Foundation","doi-asserted-by":"publisher","award":["4202034"],"award-info":[{"award-number":["4202034"]}],"id":[{"id":"10.13039\/501100004826","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Image Process."],"published-print":{"date-parts":[[2020]]},"DOI":"10.1109\/tip.2020.3013142","type":"journal-article","created":{"date-parts":[[2020,8,5]],"date-time":"2020-08-05T20:59:18Z","timestamp":1596661158000},"page":"8251-8263","source":"Crossref","is-referenced-by-count":16,"title":["ORDNet: Capturing Omni-Range Dependencies for Scene Parsing"],"prefix":"10.1109","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8996-9907","authenticated-orcid":false,"given":"Shaofei","family":"Huang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9180-2935","authenticated-orcid":false,"given":"Si","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Tianrui","family":"Hui","sequence":"additional","affiliation":[]},{"given":"Jizhong","family":"Han","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5980-4861","authenticated-orcid":false,"given":"Bo","family":"Li","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6843-0064","authenticated-orcid":false,"given":"Jiashi","family":"Feng","sequence":"additional","affiliation":[]},{"given":"Shuicheng","family":"Yan","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc NeurIPS"},{"key":"ref38","article-title":"Multi-scale context aggregation by dilated convolutions","author":"yu","year":"2015","journal-title":"arXiv 1511 07122"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref32","first-page":"1","article-title":"BAM: Bottleneck attention module","author":"park","year":"2018","journal-title":"Proc BMVC"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00745"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-009-0275-4"},{"key":"ref36","article-title":"Pytorch: An imperative style, high-performance deep learning library","author":"paszke","year":"2019","journal-title":"Proc NeurIPS"},{"key":"ref35","first-page":"1623","article-title":"Learning submodular losses with the lov&#x00E1;sz hinge","author":"yu","year":"2015","journal-title":"Proc ICML"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00085"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2011.6126343"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2644615"},{"key":"ref28","article-title":"Self-attention generative adversarial networks","author":"zhang","year":"2018","journal-title":"arXiv 1805 08318"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00069"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/3240508.3240636"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.544"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.660"},{"key":"ref20","article-title":"Neural machine translation by jointly learning to align and translate","author":"bahdanau","year":"2014","journal-title":"arXiv 1409 0473"},{"key":"ref22","first-page":"289","article-title":"Hierarchical question-image co-attention for visual question answering","author":"lu","year":"2016","journal-title":"Proc NeurIPS"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D15-1166"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.10"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.540"},{"key":"ref26","first-page":"5998","article-title":"Attention is all you need","author":"vaswani","year":"2017","journal-title":"Proc NeurIPS"},{"key":"ref25","first-page":"2048","article-title":"Show, attend and tell: Neural image caption generation with visual attention","author":"xu","year":"2015","journal-title":"Proc ICML"},{"key":"ref50","article-title":"Bridging category-level and instance-level semantic image segmentation","author":"wu","year":"2016","journal-title":"arXiv 1605 06885"},{"key":"ref51","article-title":"LabelBank: Revisiting global perspectives for semantic segmentation","author":"hu","year":"2017","journal-title":"arXiv 1703 09891"},{"key":"ref59","first-page":"740","article-title":"Microsoft coco: Common objects in context","author":"lin","year":"2014","journal-title":"Proc ECCV"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00909"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00324"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00254"},{"key":"ref55","first-page":"1853","article-title":"Symbolic graph reasoning meets convolutions","author":"liang","year":"2018","journal-title":"Proc NeurIPS"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01219-9_37"},{"key":"ref53","article-title":"Wider or deeper: Revisiting the ResNet model for visual recognition","author":"wu","year":"2016","journal-title":"arXiv 1611 10080"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.549"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.119"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00132"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.396"},{"key":"ref12","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014","journal-title":"arXiv 1409 1556"},{"key":"ref13","article-title":"Semantic image segmentation with deep convolutional nets and fully connected CRFs","author":"chen","year":"2014","journal-title":"arXiv 1412 7062"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/s00034-019-01110-4"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2018.8462243"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2019.8803037"},{"key":"ref17","article-title":"Rethinking atrous convolution for semantic image segmentation","author":"chen","year":"2017","journal-title":"arXiv 1706 05587"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00747"},{"key":"ref19","article-title":"Interlaced sparse self-attention for semantic segmentation","author":"huang","year":"2019","journal-title":"arXiv 1907 12273"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.224"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.287"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2699184"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00326"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00813"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2712691"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00064"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46475-6_33"},{"key":"ref45","article-title":"Top-down learning for structured labeling with convolutional pseudoprior","author":"xie","year":"2015","journal-title":"arXiv 1511 07409"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.348"},{"key":"ref47","article-title":"PixelNet: Towards a general pixel-level architecture","author":"bansal","year":"2016","journal-title":"arXiv 1609 06694"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.179"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00060"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.191"},{"key":"ref43","article-title":"ParseNet: Looking wider to see better","author":"liu","year":"2015","journal-title":"arXiv 1506 04579"}],"container-title":["IEEE Transactions on Image Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/83\/8835130\/09159901.pdf?arnumber=9159901","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T14:39:00Z","timestamp":1651070340000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9159901\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":62,"URL":"https:\/\/doi.org\/10.1109\/tip.2020.3013142","relation":{},"ISSN":["1057-7149","1941-0042"],"issn-type":[{"type":"print","value":"1057-7149"},{"type":"electronic","value":"1941-0042"}],"subject":[],"published":{"date-parts":[[2020]]}}}