{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T15:37:19Z","timestamp":1761061039211},"reference-count":45,"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\/wacv45572.2020.9093481","type":"proceedings-article","created":{"date-parts":[[2020,5,15]],"date-time":"2020-05-15T03:41:09Z","timestamp":1589514069000},"page":"584-593","source":"Crossref","is-referenced-by-count":22,"title":["Few-Shot Learning of Video Action Recognition Only Based on Video Contents"],"prefix":"10.1109","author":[{"given":"Yang","family":"Bo","sequence":"first","affiliation":[]},{"given":"Yangdi","family":"Lu","sequence":"additional","affiliation":[]},{"given":"Wenbo","family":"He","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.441"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2011.5995407"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.522"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206721"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/2733373.2806226"},{"key":"ref30","first-page":"843","article-title":"Unsupervised learning of video representations using lstms","author":"srivastava","year":"2015","journal-title":"International Conference on Machine Learning"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2712608"},{"key":"ref36","article-title":"Long-term temporal convolutions for action recognition","author":"varol","year":"2017","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00675"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.510"},{"key":"ref10","first-page":"249","article-title":"Understanding the difficulty of training deep feedforward neural networks","author":"glorot","year":"2010","journal-title":"Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7299059"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.521"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.59"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33715-4_31"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.604"},{"key":"ref16","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014","journal-title":"arXiv preprint arXiv 1412 6980"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.5244\/C.22.99"},{"key":"ref18","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Advances in neural information processing systems"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2011.6126543"},{"key":"ref28","first-page":"568","article-title":"Two-stream convolutional networks for action recognition in videos","author":"simonyan","year":"2014","journal-title":"Advances in neural information processing systems"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298878"},{"key":"ref27","article-title":"Temporal gaussian mixture layer for videos","author":"piergiovanni","year":"2018","journal-title":"arXiv preprint arXiv 1803 06316"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/11744047_33"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.787"},{"key":"ref29","article-title":"Ucf101: A dataset of 101 human actions classes from videos in the wild","author":"soomro","year":"2012","journal-title":"arXiv preprint arXiv 1212 0402"},{"key":"ref5","first-page":"3468","article-title":"Spatiotemporal residual networks for video action recognition","author":"feichtenhofer","year":"2016","journal-title":"Advances in neural information processing systems"},{"key":"ref8","first-page":"34","article-title":"Attentional pooling for action recognition","author":"girdhar","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7299176"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.502"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.337"},{"key":"ref1","article-title":"Delving deeper into convolutional networks for learning video representations","author":"ballas","year":"2015","journal-title":"arXiv preprint arXiv 1511 05271"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-005-1838-7"},{"key":"ref45","first-page":"9436","article-title":"To-wards universal representation for unseen action recognition","author":"zhu","year":"2018","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01231-1_32"},{"key":"ref21","first-page":"1","article-title":"Learning realistic human actions from movies","author":"laptev","year":"2008","journal-title":"Computer Vision and Pattern Recognition 2008 CVPR 2008 IEEE Conference on"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/2733373.2806222"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.476"},{"key":"ref41","first-page":"20","article-title":"Temporal segment networks: Towards good practices for deep action recognition","author":"wang","year":"2016","journal-title":"European Conference on Computer Vision"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2009.5457659"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-74936-3_22"},{"key":"ref26","first-page":"5304","article-title":"Learning latent superevents to detect multiple activities in videos","author":"piergiovanni","year":"2018","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7299101"},{"key":"ref25","doi-asserted-by":"crossref","DOI":"10.1609\/aaai.v31i1.11240","article-title":"Learning latent subevents in activity videos using temporal attention filters","author":"piergiovanni","year":"2017","journal-title":"Thirty-First AAAI Conference on Artificial Intelligence"}],"event":{"name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","start":{"date-parts":[[2020,3,1]]},"location":"Snowmass Village, CO, USA","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\/09093481.pdf?arnumber=9093481","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,23]],"date-time":"2022-10-23T19:44:10Z","timestamp":1666554250000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9093481\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3]]},"references-count":45,"URL":"https:\/\/doi.org\/10.1109\/wacv45572.2020.9093481","relation":{},"subject":[],"published":{"date-parts":[[2020,3]]}}}