{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T01:06:55Z","timestamp":1740100015466,"version":"3.37.3"},"reference-count":36,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,10,13]],"date-time":"2020-10-13T00:00:00Z","timestamp":1602547200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,10,13]],"date-time":"2020-10-13T00:00:00Z","timestamp":1602547200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,10,13]],"date-time":"2020-10-13T00:00:00Z","timestamp":1602547200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100006754","name":"Army Research Laboratory","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006754","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000183","name":"Army Research Office","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000183","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,10,13]]},"DOI":"10.1109\/aipr50011.2020.9425188","type":"proceedings-article","created":{"date-parts":[[2021,5,11]],"date-time":"2021-05-11T00:46:09Z","timestamp":1620693969000},"page":"1-6","source":"Crossref","is-referenced-by-count":0,"title":["SMVNet: Deep Learning Architectures for Accurate and Robust Multi-View Stereopsis"],"prefix":"10.1109","author":[{"given":"Shizeng","family":"Yao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yangyang","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hadi","family":"AliAkbarpour","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guna","family":"Seetharaman","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Raghuveer","family":"Rao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kannappan","family":"Palaniappan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.4304\/jmm.2.4.20-33"},{"key":"ref32","first-page":"869","article-title":"k-mle: A fast algorithm for learning statistical mixture models","author":"nielsen","year":"2012","journal-title":"IEEE International Conference on Acoustics Speech and Signal Processing"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.253"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.176"},{"year":"0","key":"ref36","article-title":"Keras: The python deep learning library"},{"year":"0","key":"ref35","article-title":"Tensorflow: An end-to-end open source machine learning platform"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-007-0107-3"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.445"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46487-9_31"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2006.19"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-008-0134-8"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2008.4587792"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2006.199"},{"key":"ref16","first-page":"73","article-title":"Iterative multi-view plane fitting","author":"habbecke","year":"2006","journal-title":"Int Fall Workshop of Vision Modeling and Visualization"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2010.5539802"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-005-3953-x"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-006-8671-5"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00298"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2009.161"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01237-3_47"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-007-0086-4"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.19"},{"key":"ref29","first-page":"3279","article-title":"Matchnet: Unifying feature and metric learning for patch-based matching","author":"han","year":"2015","journal-title":"CVPR"},{"key":"ref5","first-page":"2366","article-title":"Depth map prediction from a single image using a multi-scale deep network","author":"eigen","year":"2014","journal-title":"Advances in neural information processing systems"},{"key":"ref8","first-page":"365","article-title":"Learning a multi-view stereo machine","author":"kar","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2017.00017"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2004.03.016"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3072959.3073599"},{"journal-title":"Variational Principles Surface evolution PDE’s Level Set Methods and the Stereo problem","year":"2002","author":"faugeras","key":"ref1"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/11744047_17"},{"key":"ref22","first-page":"7297","article-title":"Densepose: Dense human pose estimation in the wild","author":"alp g\u00fcler","year":"2018","journal-title":"CVPR"},{"key":"ref21","article-title":"Pointnet: Deep learning on point sets for 3d classification and segmentation","author":"qi","year":"2017","journal-title":"CVPR"},{"key":"ref24","first-page":"5515","article-title":"Deepstereo: Learning to predict new views from the world’s imagery","author":"flynn","year":"2016","journal-title":"CVPR"},{"article-title":"Sfm-net: Learning of structure and motion from video","year":"2017","author":"vijayanarasimhan","key":"ref23"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.336"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2016.7487679"}],"event":{"name":"2020 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","start":{"date-parts":[[2020,10,13]]},"location":"Washington DC, DC, USA","end":{"date-parts":[[2020,10,15]]}},"container-title":["2020 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9424928\/9425032\/09425188.pdf?arnumber=9425188","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,27]],"date-time":"2022-06-27T15:47:08Z","timestamp":1656344828000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9425188\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,13]]},"references-count":36,"URL":"https:\/\/doi.org\/10.1109\/aipr50011.2020.9425188","relation":{},"subject":[],"published":{"date-parts":[[2020,10,13]]}}}