{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T15:00:50Z","timestamp":1761663650533,"version":"3.28.0"},"reference-count":32,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,5]]},"DOI":"10.1109\/icra.2017.7989162","type":"proceedings-article","created":{"date-parts":[[2017,7,25]],"date-time":"2017-07-25T17:44:28Z","timestamp":1501004668000},"page":"1362-1369","source":"Crossref","is-referenced-by-count":17,"title":["A deep representation for depth images from synthetic data"],"prefix":"10.1109","author":[{"given":"Fabio Maria","family":"Carlucci","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paolo","family":"Russo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Barbara","family":"Caputo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref32","article-title":"Benchmarking large-scale fine-grained categorization","author":"anelia","year":"2014","journal-title":"IEEE Winter conference on Applications of Computer Vision IEEE"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2012.6248364"},{"key":"ref30","article-title":"Convolutional-recursive deep learning for 3d object classification","author":"socher","year":"2012","journal-title":"NIPS"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2015.05.007"},{"key":"ref11","article-title":"A large-scale hierarchical multi-view rgb-d object dataset","author":"kevin","year":"2011","journal-title":"Robotics and Automation (ICRA) 2011 IEEE International Conference On IEEE"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7299125"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1023\/B:VISI.0000029664.99615.94"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2012.6225188"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2015.7139358"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2014.131"},{"key":"ref17","article-title":"Learning Deep Features for Scene Recognition using Places Database","author":"zhou","year":"2014","journal-title":"Advances in Neural Information Processing Systems I (NIPS)"},{"key":"ref18","first-page":"345360","article-title":"Learning rich features from RGB-D images for object detection and segmentation","author":"gupta","year":"2014","journal-title":"Proc ECCV"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.95"},{"key":"ref28","article-title":"Caffe: Convolutional architecture for fast feature embedding","author":"yangqing","year":"2014","journal-title":"Proceedings of the ACM International Conference on Multimedia ACM"},{"key":"ref4","article-title":"Convolutional fisher kernels for rgb-d object recognition","author":"yanhua","year":"2015","journal-title":"3D Vision (3DV) 2015 International Conference on"},{"key":"ref27","article-title":"Online-batch strongly convex multi kernel learning","author":"francesco","year":"2010","journal-title":"Computer Vision and Pattern Recognition (CVPR) 2010 IEEE Conference On IEEE"},{"key":"ref3","first-page":"665673","article-title":"Convolutional-recursive deep learning for 3D object classification","author":"socher","year":"2012","journal-title":"Proc NIPS"},{"key":"ref6","article-title":"RGB-D object recognition and pose estimation based on pre-trained convolutional neural network features","author":"max","year":"2015","journal-title":"2015 IEEE International Conference on Robotics and Automation (ICRA) IEEE"},{"key":"ref29","first-page":"25792605","article-title":"Visualizing data using t-SNE","volume":"9","author":"van","year":"2008","journal-title":"Journal of Machine Learning Research"},{"article-title":"ImageNet large scale visual recognition challenge","year":"2014","author":"russakovsky","key":"ref5"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2016.7487310"},{"key":"ref7","article-title":"Multimodal deep learning for robust rgb-d object recognition","author":"andreas","year":"2015","journal-title":"Intelligent Robots and Systems (IROS) 2015 IEEE\/RSJ International Conference on IEEE"},{"key":"ref2","first-page":"18171824","article-title":"A large-scale hierarchical multiview RGB-D object dataset","author":"lai","year":"2011","journal-title":"Proc ICRA"},{"key":"ref9","article-title":"Semisupervised learning for rgb-d object recognition","author":"cheng","year":"2014","journal-title":"ICPR"},{"key":"ref1","article-title":"Imagenet classification with deep convolutional neural networks","author":"alex","year":"2012","journal-title":"Advances in neural information processing systems"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2015.7353481"},{"key":"ref22","article-title":"A benchmark for RGB-D visual odometry, 3D reconstruction and SLAM","author":"ankur","year":"2014","journal-title":"Robotics and Automation (ICRA) 2014 IEEE International Conference On IEEE"},{"key":"ref21","article-title":"3D ShapeNets: A Deep Representation for Volumetric Shape Modeling","author":"wu","year":"0","journal-title":"Proceedings of 28th IEEE Conference on Computer Vision and Pattern Recognition (CVPR2015)"},{"key":"ref24","article-title":"Going deeper with convolutions","author":"christian","year":"2015","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"article-title":"Very deep convolutional networks for large-scale image recognition","year":"2014","author":"karen","key":"ref23"},{"article-title":"Good Practice in CNN Feature Transfer","year":"2016","author":"liang","key":"ref26"},{"article-title":"Deep residual learning for image recognition","year":"2015","author":"kaiming","key":"ref25"}],"event":{"name":"2017 IEEE International Conference on Robotics and Automation (ICRA)","start":{"date-parts":[[2017,5,29]]},"location":"Singapore, Singapore","end":{"date-parts":[[2017,6,3]]}},"container-title":["2017 IEEE International Conference on Robotics and Automation (ICRA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7960754\/7988677\/07989162.pdf?arnumber=7989162","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,10,2]],"date-time":"2017-10-02T21:59:10Z","timestamp":1506981550000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/7989162\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,5]]},"references-count":32,"URL":"https:\/\/doi.org\/10.1109\/icra.2017.7989162","relation":{},"subject":[],"published":{"date-parts":[[2017,5]]}}}