{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T18:33:50Z","timestamp":1776278030365,"version":"3.50.1"},"reference-count":48,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"4","license":[{"start":{"date-parts":[[2021,10,1]],"date-time":"2021-10-01T00:00:00Z","timestamp":1633046400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,10,1]],"date-time":"2021-10-01T00:00:00Z","timestamp":1633046400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,10,1]],"date-time":"2021-10-01T00:00:00Z","timestamp":1633046400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Visvesvaraya PhD Scheme MeitY"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Robot. Autom. Lett."],"published-print":{"date-parts":[[2021,10]]},"DOI":"10.1109\/lra.2021.3101049","type":"journal-article","created":{"date-parts":[[2021,7,30]],"date-time":"2021-07-30T20:16:34Z","timestamp":1627676194000},"page":"7791-7798","source":"Crossref","is-referenced-by-count":26,"title":["ADAADepth: Adapting Data Augmentation and Attention for Self-Supervised Monocular Depth Estimation"],"prefix":"10.1109","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6729-4857","authenticated-orcid":false,"given":"Vinay","family":"Kaushik","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8844-9237","authenticated-orcid":false,"given":"Kartik","family":"Jindgar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2677-3071","authenticated-orcid":false,"given":"Brejesh","family":"Lall","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00031"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00594"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.304"},{"key":"ref32","article-title":"A simple neural network module for relational reasoning","author":"santoro","year":"0"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00718"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00069"},{"key":"ref37","article-title":"Unsupervised learning of geometry with edge-aware depth-normal consistency","author":"yang","year":"0"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2003.819861"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00216"},{"key":"ref34","first-page":"234","article-title":"U-net: Convolutional networks for biomedical image segmentation","author":"ronneberger","year":"2015","journal-title":"Proc Int Conf Med Image Comput Comput -Assist Intervention"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00256"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00043"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00481"},{"key":"ref12","article-title":"SfM-Net: Learning of structure and motion from video","author":"vijayanarasimhan","year":"0"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.700"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2019.2930258"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2008.132"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2014.2316835"},{"key":"ref17","article-title":"Size-to-depth: A new perspective for single image depth estimation","author":"wu","year":"0"},{"key":"ref18","article-title":"Single-image depth perception in the wild","author":"chen","year":"0"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00225"},{"key":"ref28","first-page":"7354","article-title":"Self-attention generative adversarial networks","author":"zhang","year":"2019","journal-title":"Proc Int Conf Mach Learn PMLR"},{"key":"ref4","first-page":"2366","article-title":"Depth map prediction from a single image using a multi-scale deep network","volume":"27","author":"eigen","year":"2014","journal-title":"Proc Adv Neural Info Process Syst"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00813"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICEIC49074.2020.9051031"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.699"},{"key":"ref29","article-title":"Attention u-net: Learning where to look for the pancreas","author":"oktay","year":"0"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00214"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00393"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46484-8_45"},{"key":"ref2","article-title":"Deep 3D-Zoom Net: Unsupervised learning of photo-realistic 3d-zoom","author":"bello","year":"0"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00212"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.3390\/s20020532"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.97"},{"key":"ref20","first-page":"12626","article-title":"Forget about the lidar: Self-supervised depth estimators with med probability volumes","volume":"33","author":"gonzalezbello","year":"2020","journal-title":"Proc Adv Neural Info Process Syst"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2014.2316835"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00216"},{"key":"ref22","article-title":"Unsupervised scale-consistent depth and ego-motion learning from monocular video","author":"bian","year":"0"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2016.32"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00716"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1177\/0278364913491297"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58529-7_34"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33018001"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58577-8_4"},{"key":"ref44","doi-asserted-by":"crossref","first-page":"824","DOI":"10.1109\/TPAMI.2008.132","article-title":"Make3D: learning 3D scene structure from a single still image","volume":"31","author":"saxena","year":"2008","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00069"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8793621"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58574-7_35"}],"container-title":["IEEE Robotics and Automation Letters"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7083369\/9475905\/09502529.pdf?arnumber=9502529","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T14:54:08Z","timestamp":1652194448000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9502529\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10]]},"references-count":48,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.1109\/lra.2021.3101049","relation":{},"ISSN":["2377-3766","2377-3774"],"issn-type":[{"value":"2377-3766","type":"electronic"},{"value":"2377-3774","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,10]]}}}