{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T12:57:56Z","timestamp":1780318676472,"version":"3.54.1"},"reference-count":64,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,3,1]],"date-time":"2020-03-01T00:00:00Z","timestamp":1583020800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,3,1]],"date-time":"2020-03-01T00:00:00Z","timestamp":1583020800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,3,1]],"date-time":"2020-03-01T00:00:00Z","timestamp":1583020800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,3]]},"DOI":"10.1109\/wacv45572.2020.9093545","type":"proceedings-article","created":{"date-parts":[[2020,5,15]],"date-time":"2020-05-15T03:41:09Z","timestamp":1589514069000},"page":"912-922","source":"Crossref","is-referenced-by-count":51,"title":["Transductive Zero-Shot Learning for 3D Point Cloud Classification"],"prefix":"10.1109","author":[{"given":"Ali","family":"Cheraghian","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shafin","family":"Rahman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dylan","family":"Campbell","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lars","family":"Petersson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","article-title":"Spectralgans for high-resolution 3d point-cloud generation","author":"ramasinghe","year":"2019"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-019-01278-x"},{"key":"ref33","first-page":"2487","article-title":"Hubs in space: Popular nearest neighbors in high-dimensional data","volume":"11","author":"radovanovic","year":"2010","journal-title":"Journal of Machine Learning Research"},{"key":"ref32","article-title":"Visually aligned word embeddings for improving zero-shot learning","author":"qiao","year":"2017","journal-title":"British Conference on Machine Vision (BMVC)"},{"key":"ref31","first-page":"5099","article-title":"Pointnet++: Deep hierarchical feature learning on point sets in a metric space","author":"qi","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref30","first-page":"4","article-title":"Pointnet: Deep learning on point sets for 3d classification and segmentation","volume":"1","author":"qi","year":"2017","journal-title":"Proc Computer Vision and Pattern Recognition (CVPR)"},{"key":"ref37","article-title":"Blended convolution and synthesis for efficient discrimination of 3d shapes","author":"ramasinghe","year":"2019"},{"key":"ref36","article-title":"Zero-shot object detection: Learning to simultaneously recognize and localize novel concepts","author":"rahman","year":"2018","journal-title":"Asian Conference on Computer Vision (ACCV)"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2861573"},{"key":"ref34","article-title":"Deep multiple instance learning for zero-shot image tagging","author":"rahman","year":"2018","journal-title":"Asian Conference on Computer Vision (ACCV)"},{"key":"ref60","article-title":"A unified perspective on multidomain and multi-task learning","author":"yang","year":"2015","journal-title":"International Conference on Learning Representations (ICLR)"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2017.8202207"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2017.2751741"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.321"},{"key":"ref28","article-title":"Zero-shot learning by convex combination of semantic embeddings","author":"norouzi","year":"2014","journal-title":"ICLRE"},{"key":"ref64","article-title":"Domain-invariant projection learning for zero-shot recognition","author":"zhao","year":"2018","journal-title":"Advances in Neural Information Processing Systems (NIPS)"},{"key":"ref27","first-page":"3111","article-title":"Distributed representations of words and phrases and their compositionality","author":"mikolov","year":"2013","journal-title":"NIPS"},{"key":"ref29","first-page":"1410","article-title":"Zero-shot learning with semantic output codes","author":"palatucci","year":"2009","journal-title":"NIPS"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2487986"},{"key":"ref1","first-page":"265","article-title":"Tensor-flow: a system for large-scale machine learning","author":"abadi","year":"2016","journal-title":"OSDI"},{"key":"ref20","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00170"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.140"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00979"},{"key":"ref23","article-title":"Pseudo-label : The simple and efficient semi-supervised learning method for deep neural networks","author":"lee","year":"2013","journal-title":"Proceedings of ICML 2013 Workshop on Challenges in Representation Learning"},{"key":"ref26","article-title":"Non-rigid 3D Shape Retrieval","author":"lian","year":"2015","journal-title":"Eurographics Workshop on 3D Object Retrieval"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33018682"},{"key":"ref50","first-page":"3221","article-title":"Accelerating t-sne using tree-based algorithms","volume":"15","author":"van der maaten","year":"2014","journal-title":"Journal of Machine Learning Research"},{"key":"ref51","article-title":"The Caltech-UCSD Birds-200-2011 Dataset","author":"wah","year":"2011","journal-title":"Technical Report CNS-TR-2011-001"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01237-3_6"},{"key":"ref58","article-title":"Attentional shapecon-textnet for point cloud recognition","author":"xie","year":"2018","journal-title":"The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01052"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00581"},{"key":"ref55","first-page":"1","article-title":"Zero-shot learning - a comprehensive evaluation of the good, the bad and the ugly","author":"xian","year":"2018","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"ref54","first-page":"1912","article-title":"3d shapenets: A deep representation for volumetric shapes","author":"wu","year":"0","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"ref53","article-title":"Dynamic graph cnn for learning on point clouds","author":"wang","year":"2018"},{"key":"ref52","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-030-01225-0_4","article-title":"Local spectral graph convolution for point set feature learning","author":"wang","year":"2018"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01065"},{"key":"ref40","first-page":"46","article-title":"Transfer learning in a transductive setting","author":"rohrbach","year":"2013","journal-title":"NIPS"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01261-8_28"},{"key":"ref13","article-title":"Devise: A deep visual-semantic embedding model","author":"frome","year":"2013","journal-title":"NIPS"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2408354"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00208"},{"key":"ref17","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"ioffe","year":"2015"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/2047196.2047270"},{"key":"ref19","first-page":"2017","article-title":"Spatial transformer networks","author":"jaderberg","year":"2015","journal-title":"Advances in Neural IInformation Processing Systems"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.575"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298911"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.3390\/rs10020328"},{"key":"ref5","first-page":"52","author":"chao","year":"2016","journal-title":"An empirical study and analysis of generalized zero-shot learning for object recognition in the wild"},{"key":"ref8","article-title":"Mitigating the hubness problem for zero-shot learning of 3d objects","author":"cheraghian","year":"2019","journal-title":"British Conference on Machine Vision (BMVC)"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2019.00132"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2019.02.027"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.23919\/MVA.2019.8758063"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1007\/s00138-007-0097-8"},{"key":"ref45","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1007\/978-3-319-23528-8_9","article-title":"Ridge regression, hubness, and zero-shot learning","author":"shigeto","year":"2015","journal-title":"Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00113"},{"key":"ref47","first-page":"935","article-title":"Zero-shot learning through cross-modal transfer","author":"socher","year":"2013","journal-title":"NIPS"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref41","first-page":"2152","article-title":"An embarrassingly simple approach to zero-shot learning","author":"romera-paredes","year":"2015","journal-title":"ICML"},{"key":"ref44","doi-asserted-by":"crossref","first-page":"815","DOI":"10.1109\/CVPR.2015.7298682","article-title":"Facenet: A unified embedding for face recognition and clustering","author":"schroff","year":"2015","journal-title":"2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00844"}],"event":{"name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","location":"Snowmass Village, CO, USA","start":{"date-parts":[[2020,3,1]]},"end":{"date-parts":[[2020,3,5]]}},"container-title":["2020 IEEE Winter Conference on Applications of Computer Vision (WACV)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9087828\/9093261\/09093545.pdf?arnumber=9093545","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,30]],"date-time":"2022-06-30T15:18:48Z","timestamp":1656602328000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9093545\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3]]},"references-count":64,"URL":"https:\/\/doi.org\/10.1109\/wacv45572.2020.9093545","relation":{},"subject":[],"published":{"date-parts":[[2020,3]]}}}