{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T20:18:35Z","timestamp":1740169115823,"version":"3.37.3"},"reference-count":34,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2019]]},"DOI":"10.1109\/access.2019.2947195","type":"journal-article","created":{"date-parts":[[2019,10,14]],"date-time":"2019-10-14T23:21:58Z","timestamp":1571095318000},"page":"150306-150317","source":"Crossref","is-referenced-by-count":5,"title":["Octave Deep Plane-Sweeping Network: Reducing Spatial Redundancy for Learning-Based Plane-Sweeping Stereo"],"prefix":"10.1109","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6526-0802","authenticated-orcid":false,"given":"Ren","family":"Komatsu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7051-1194","authenticated-orcid":false,"given":"Hiromitsu","family":"Fujii","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yusuke","family":"Tamura","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Atsushi","family":"Yamashita","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hajime","family":"Asama","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-016-0902-9"},{"key":"ref32","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 Adv Neural Inf Process Syst"},{"key":"ref31","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014","journal-title":"arXiv 1412 6980"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.272"},{"key":"ref34","doi-asserted-by":"crossref","DOI":"10.1145\/3072959.3073599","article-title":"Tanks and temples: Benchmarking large-scale scene reconstruction","volume":"36","author":"knapitsch","year":"2017","journal-title":"ACM Trans Graph"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00298"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00567"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2018.00037"},{"key":"ref13","article-title":"GPipe: Efficient training of giant neural networks using pipeline parallelism","author":"huang","year":"2018","journal-title":"arXiv 1811 06965"},{"key":"ref14","article-title":"Drop an Octave: Reducing spatial redundancy in convolutional neural networks with octave convolution","author":"chen","year":"2019","journal-title":"arXiv 1904 05049"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00745"},{"key":"ref16","first-page":"109","article-title":"Efficient inference in fully connected CRFs with Gaussian edge potentials","author":"kr\u00e4henb\u00fchl","year":"2011","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2389824"},{"key":"ref19","first-page":"2017","article-title":"Spatial transformer networks","author":"jaderberg","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.596"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.1996.517097"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.158"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/34.206955"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.17"},{"key":"ref29","article-title":"ShapeNet: An information-rich 3D model repository","author":"chang","year":"2015","journal-title":"arXiv 1512 03012"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2007.383245"},{"key":"ref8","first-page":"767","article-title":"MVSNET: Depth inference for unstructured multi-view stereo","author":"yao","year":"2018","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00567"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1038\/293133a0","article-title":"A computer algorithm for reconstructing a scene from two projections","volume":"293","author":"longuet-higgins","year":"1981","journal-title":"Nature"},{"key":"ref9","first-page":"1","article-title":"DPSNet: End-to-end deep plane sweep stereo","author":"im","year":"2019","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref1","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1126\/science.968482","article-title":"Cooperative computation of stereo disparity","volume":"194","author":"marr","year":"1976","journal-title":"Science"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2867261"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.458"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177703732"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.445"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2012.6385773"},{"key":"ref26","first-page":"11","article-title":"MVE&#x2013;a multi-view reconstruction environment","author":"fuhrmann","year":"2014","journal-title":"Proceedings of the Eurographics Workshop on Graphics and Cultural Heritage"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46487-9_31"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8600701\/08867874.pdf?arnumber=8867874","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,27]],"date-time":"2022-01-27T00:43:36Z","timestamp":1643244216000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8867874\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"references-count":34,"URL":"https:\/\/doi.org\/10.1109\/access.2019.2947195","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2019]]}}}