{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T16:03:53Z","timestamp":1776182633924,"version":"3.50.1"},"reference-count":37,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,11]]},"DOI":"10.1109\/dicta.2016.7797068","type":"proceedings-article","created":{"date-parts":[[2016,12,26]],"date-time":"2016-12-26T16:44:21Z","timestamp":1482770661000},"page":"1-7","source":"Crossref","is-referenced-by-count":11,"title":["Object Depth Estimation from a Single Image Using Fully Convolutional Neural Network"],"prefix":"10.1109","author":[{"given":"Ahmed J.","family":"Afifi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Olaf","family":"Hellwich","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref33","first-page":"1602","article-title":"A large dataset of object scans","author":"choi","year":"2016","journal-title":"Arxiv preprint arXiv"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/2733373.2807412"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/S0262-8856(96)01112-2"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/BF00131148"},{"key":"ref37","article-title":"Visualizing and understanding convolutional networks","author":"zeiler","year":"2014","journal-title":"Proc Conf International Conference on Computer Vision (ICCV)"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1111\/cgf.12573"},{"key":"ref35","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-319-24947-6_15","article-title":"Joint 3D Object and Layout Inference from a single RGB-D Image","author":"geiger","year":"2015","journal-title":"German Conference on Pattern Recognition (GCPR)"},{"key":"ref34","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4471-6741-9","article-title":"Learning depth from single monocular images using deep convolutional neural fields","author":"liu","year":"2015","journal-title":"Proc Conf Computer Vision and Pattern Recognition (CVPR)"},{"key":"ref10","article-title":"Rgb-(d) scene labeling: Features and algorithms","author":"ren","year":"2012","journal-title":"Proc Conf Computer Vision and Pattern Recognition (CVPR)"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2008.132"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.97"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298897"},{"key":"ref14","article-title":"Depth extraction from video using non-parametric sampling","author":"karsch","year":"2012","journal-title":"Proc Eur Conf Comp Vis (ECCV)"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2012.6238903"},{"key":"ref16","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1023\/B:VISI.0000029664.99615.94"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2005.177"},{"key":"ref19","article-title":"Improving the fisher kernel for large-scale image classification","author":"perronnin","year":"2010","journal-title":"Proc European Conference on Computer Vision (ECCV)"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.324"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/1073204.1073232"},{"key":"ref27","first-page":"1605","article-title":"Estimating Depth from Monocular Images as Classification Using Deep Fully Convolutional Residual Networks","author":"cao","year":"2016","journal-title":"Arxiv preprint arXiv"},{"key":"ref3","article-title":"Make3d: Learning 3-d scene structure from a single still image","author":"saxena","year":"2008","journal-title":"TPAMI"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1007\/978-1-84882-935-0_7","article-title":"Structure from motion","author":"szeliski","year":"2011","journal-title":"Computer Vision Texts in Computer Science Springer London"},{"key":"ref29","first-page":"1601","article-title":"Discriminative Training of Deep Fully-connected Continuous CRF with Task-specific Loss","author":"liu","year":"2016","journal-title":"Arxiv preprint arXiv"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1002\/rob.20276"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.120"},{"key":"ref7","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":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.241"},{"key":"ref9","article-title":"Indoor segmentation and support inference from RGBD images","author":"silberman","year":"2012","journal-title":"Proc Eur Conf Comp Vis (ECCV)"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.19"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2005.1505106"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7299152"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.81"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.304"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2010.5539823"},{"key":"ref26","first-page":"1512","article-title":"Deep residual learning for image recognition","author":"he","year":"2015","journal-title":"Arxiv preprint arXiv"},{"key":"ref25","first-page":"1409","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014","journal-title":"Arxiv preprint arXiv"}],"event":{"name":"2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","location":"Gold Coast, Australia","start":{"date-parts":[[2016,11,30]]},"end":{"date-parts":[[2016,12,2]]}},"container-title":["2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7794373\/7796973\/07797068.pdf?arnumber=7797068","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,9,28]],"date-time":"2020-09-28T03:37:20Z","timestamp":1601264240000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/7797068\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,11]]},"references-count":37,"URL":"https:\/\/doi.org\/10.1109\/dicta.2016.7797068","relation":{},"subject":[],"published":{"date-parts":[[2016,11]]}}}