{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T02:32:26Z","timestamp":1730255546368,"version":"3.28.0"},"reference-count":33,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,5]]},"DOI":"10.1109\/icra.2018.8461089","type":"proceedings-article","created":{"date-parts":[[2018,9,21]],"date-time":"2018-09-21T18:28:03Z","timestamp":1537554483000},"page":"4525-4531","source":"Crossref","is-referenced-by-count":2,"title":["DPDB-Net: Exploiting Dense Connections for Convolutional Encoders"],"prefix":"10.1109","author":[{"given":"Gabriel L.","family":"Oliveira","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wolfram","family":"Burgard","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thomas","family":"Brox","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"journal-title":"Dual path networks arXiv preprint arXiv 1707 01629","year":"2017","author":"xiao","key":"ref33"},{"journal-title":"Reseg A recurrent neural network-based model for semantic segmentation In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops","year":"2016","author":"visin","key":"ref32"},{"key":"ref31","first-page":"465","article-title":"Deep multispectral semantic scene understanding of forested environments using multimodal fusion","author":"abhinav","year":"2017","journal-title":"Proceedings of the 2016 International Symposium on Experimental Robotics"},{"key":"ref30","first-page":"352","author":"tighe","year":"2010","journal-title":"SuperParsing Scalable Nonparametric Image Parsing with Superpixels"},{"journal-title":"STFCN spatio-temporal FCN for semantic video segmentation CoRR abs\/1608 05971","year":"2016","author":"fayyaz","key":"ref10"},{"key":"ref11","first-page":"1","volume":"41","author":"gao","year":"2017","journal-title":"Unsupervised learning to detect loops using deep neural networks for visual slam system Autonomous Robots"},{"journal-title":"Deep residual learning for image recognition CoRR abs\/1512 03385","year":"2015","author":"he","key":"ref12"},{"journal-title":"Weinberger Densely connected convolutional networks In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","year":"2017","author":"huang","key":"ref13"},{"journal-title":"Learning sparse high dimensional filters Image filtering dense crfs and bilateral neural networks In IEEE Conf on Computer Vision and Pattern Recognition (CVPR)","year":"2016","author":"jampani","key":"ref14"},{"journal-title":"Adam A method for stochastic optimization arXiv preprint arXiv 1412 6980","year":"2014","author":"kingma","key":"ref15"},{"key":"ref16","first-page":"1097","author":"krizhevsky","year":"2012","journal-title":"ImageNet Classification with Deep Convolutional Neural Networks"},{"key":"ref17","first-page":"739","author":"ladicky","year":"2009","journal-title":"Associative hierarchical crfs for object class image segmentation In ICCV"},{"journal-title":"Efficient piecewise training of deep structured models for semantic segmentation In IEEE Conference on Computer Vision and Pattern Recognition (CVPR&#x2018;16)","year":"2016","author":"lin","key":"ref18"},{"journal-title":"Multiclass semantic video segmentation with object-level active inference In The IEEE Conference on computer Vision and Pattern Recognition (CVPR)","year":"2015","author":"liu","key":"ref19"},{"journal-title":"Very Deep Convolutional Networks for Large-scale Image Recognition","year":"2015","author":"simonyan","key":"ref28"},{"key":"ref4","article-title":"Julien Fauqueur, and Roberto Cipolla. Semantic object classes in video: A high-definition ground truth database","author":"brostow","year":"2008","journal-title":"Pattern Recognition Letters"},{"journal-title":"U-net Convolutional networks for biomedical image segmentation Medical Image Computing and Computer-Assisted Intervention (MICCAl)","year":"2015","author":"ronneberger","key":"ref27"},{"journal-title":"The fast bilateral solver ECCV","year":"2016","author":"barron","key":"ref3"},{"journal-title":"Deeplab Semantic image segmentation with deep convolutional nets atrous convolution and fully connected crfs arXiv 1606 00915","year":"2016","author":"chen","key":"ref6"},{"journal-title":"Place recognition with ConvNet landmarks Viewpoint-robust condition-robust training-free","year":"2015","author":"suenderhauf","key":"ref29"},{"journal-title":"Semantic image segmentation with deep convolutional nets and fully connected crfs In ICLR","year":"2015","author":"chen","key":"ref5"},{"journal-title":"ImageNet A Large-scale Hierarchical Image Database","year":"2009","author":"deng","key":"ref8"},{"journal-title":"Fast and accurate deep network learning by exponential linear units (ELUs)","year":"2016","author":"clevert","key":"ref7"},{"journal-title":"Segnet A deep convolutional encoder-decoder architecture for robust semantic pixel-wise labelling arXiv preprint arXiv 1505 07293","year":"2015","author":"badrinarayanan","key":"ref2"},{"journal-title":"Flownet Learning optical flow with convolutional networks In IEEE International Conference on Computer Vision (ICCV)","year":"2015","author":"dosovitskiy","key":"ref9"},{"journal-title":"Tensorflow Large-scale machine learning on heterogeneous distributed systems ar Xiv preprint arXiv 1603 04467 2016","year":"0","author":"abadi","key":"ref1"},{"journal-title":"Parsenet Looking wider to see better arXiv preprint arXiv 1506 04579","year":"2015","author":"liu","key":"ref20"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298959"},{"journal-title":"Fully Convolutional Networks for Semantic Segmentation","year":"2015","author":"long","key":"ref21"},{"journal-title":"Efficient deep models for monocular road segmentation In IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)","year":"2016","author":"oliveira","key":"ref24"},{"key":"ref23","first-page":"1520","author":"noh","year":"2015","journal-title":"Learning deconvolution network for semantic segmentation"},{"journal-title":"Large kernel matters - improve semantic segmentation by global convolutional network In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","year":"2017","author":"peng","key":"ref26"},{"journal-title":"Efficient and robust deep networks for semantic segmentation The International Journal of Robotics Research","year":"2017","author":"oliveira","key":"ref25"}],"event":{"name":"2018 IEEE International Conference on Robotics and Automation (ICRA)","start":{"date-parts":[[2018,5,21]]},"location":"Brisbane, QLD","end":{"date-parts":[[2018,5,25]]}},"container-title":["2018 IEEE International Conference on Robotics and Automation (ICRA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8449910\/8460178\/08461089.pdf?arnumber=8461089","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,8,23]],"date-time":"2020-08-23T21:42:53Z","timestamp":1598218973000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8461089\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,5]]},"references-count":33,"URL":"https:\/\/doi.org\/10.1109\/icra.2018.8461089","relation":{},"subject":[],"published":{"date-parts":[[2018,5]]}}}