{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,6]],"date-time":"2026-06-06T16:52:50Z","timestamp":1780764770569,"version":"3.54.1"},"reference-count":28,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2020,4,1]],"date-time":"2020-04-01T00:00:00Z","timestamp":1585699200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,4,1]],"date-time":"2020-04-01T00:00:00Z","timestamp":1585699200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,4,1]],"date-time":"2020-04-01T00:00:00Z","timestamp":1585699200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"HILTI group"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Robot. Autom. Lett."],"published-print":{"date-parts":[[2020,4]]},"DOI":"10.1109\/lra.2020.2967313","type":"journal-article","created":{"date-parts":[[2020,1,17]],"date-time":"2020-01-17T20:57:20Z","timestamp":1579294640000},"page":"1032-1038","source":"Crossref","is-referenced-by-count":19,"title":["Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes"],"prefix":"10.1109","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6393-2513","authenticated-orcid":false,"given":"Nicolas","family":"Marchal","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7629-0006","authenticated-orcid":false,"given":"Charlotte","family":"Moraldo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1713-7877","authenticated-orcid":false,"given":"Hermann","family":"Blum","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2760-7983","authenticated-orcid":false,"given":"Roland","family":"Siegwart","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2972-6011","authenticated-orcid":false,"given":"Cesar","family":"Cadena","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2919-4040","authenticated-orcid":false,"given":"Abel","family":"Gawel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref10","first-page":"10\ufffd236","article-title":"Glow: Generative flow with invertible 1?&#x00D7;?1 convolutions","author":"kingma","year":"0","journal-title":"Proc Advances Neural Inf Process Syst"},{"key":"ref11","article-title":"The fishyscapes benchmark: Measuring blind spots in semantic segmentation","author":"blum","year":"2019","journal-title":"arXiv 1904 03215"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.178"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.322"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2577031"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2019.2923960"},{"key":"ref17","article-title":"SegNet: A deep convolutional encoder-decoder architecture for robust semantic pixel-wise labelling","author":"badrinarayanan","year":"2015","journal-title":"arXiv 1505 07293"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.rti.2004.12.004"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2018.2805811"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2008.4563100"},{"key":"ref4","article-title":"Waic, but why? generative ensembles for robust anomaly detection","author":"choi","year":"2018","journal-title":"arXiv 1810 01392"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-009-0275-4"},{"key":"ref3","first-page":"7167","article-title":"A simple unified framework for detecting out-of-distribution samples and adversarial attacks","author":"lee","year":"0","journal-title":"Advances Neural Inf Process Syst"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.jss.2019.02.021"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.173"},{"key":"ref8","article-title":"Nice: Non-linear independent components estimation","author":"dinh","year":"0","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8794371"},{"key":"ref2","article-title":"A baseline for detecting misclassified and out-of-distribution examples in neural networks","author":"hendrycks","year":"0","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref9","article-title":"Density estimation using real NVP","author":"dinh","year":"0","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref1","first-page":"373","article-title":"Dense object nets: Learning dense visual object descriptors by and for robotic manipulation","author":"florence","year":"0","journal-title":"Proc 87th Mach Learn Res"},{"key":"ref20","article-title":"Uncertainty in deep learning","author":"gal","year":"2016"},{"key":"ref22","article-title":"Deep k-nearest neighbors: Towards confident, interpretable and robust deep learning","author":"papernot","year":"2018","journal-title":"arXiv 1803 04765"},{"key":"ref21","first-page":"5574","article-title":"What uncertainties do we need in bayesian deep learning for computer vision","author":"kendall","year":"0","journal-title":"Proc Advances Neural Inf Process Syst"},{"key":"ref24","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"0","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref23","first-page":"746","article-title":"Indoor segmentation and support inference from rgbd images","author":"silberman","year":"0","journal-title":"Proc Eur Conf Comput Vision"},{"key":"ref26","article-title":"Distance-based confidence score for neural network classifiers","author":"mandelbaum","year":"2017","journal-title":"arXiv 1709 09844"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.544"}],"container-title":["IEEE Robotics and Automation Letters"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7083369\/8932682\/08962043.pdf?arnumber=8962043","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T17:32:59Z","timestamp":1651080779000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8962043\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,4]]},"references-count":28,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/lra.2020.2967313","relation":{},"ISSN":["2377-3766","2377-3774"],"issn-type":[{"value":"2377-3766","type":"electronic"},{"value":"2377-3774","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,4]]}}}