{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T11:58:48Z","timestamp":1761998328577,"version":"build-2065373602"},"reference-count":25,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,7]]},"DOI":"10.1109\/icmew.2017.8026278","type":"proceedings-article","created":{"date-parts":[[2017,9,7]],"date-time":"2017-09-07T20:34:59Z","timestamp":1504816499000},"page":"591-596","source":"Crossref","is-referenced-by-count":5,"title":["Learning robust representations using recurrent neural networks for skeleton based action classification and detection"],"prefix":"10.1109","author":[{"family":"Hongsong Wang","sequence":"first","affiliation":[]},{"family":"Liang Wang","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ICEEI.2011.6021605"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2012.6239234"},{"key":"ref12","article-title":"Human activity detection from rgbd images","author":"sung","year":"2011","journal-title":"Plan Activity and Intent Recognition"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2016.2552404"},{"key":"ref14","doi-asserted-by":"crossref","DOI":"10.1609\/aaai.v31i1.11212","article-title":"An end-to-end spatio-temporal attention model for human action recognition from skeleton data","author":"song","year":"2017","journal-title":"AAAI"},{"key":"ref15","article-title":"Action points: A representation for low-latency online human action recognition","author":"nowozin","year":"2012","journal-title":"Tech Rep MSR-TR-2012-68"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2015.138"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/2648583"},{"key":"ref18","article-title":"Discriminative orderlet mining for real-time recognition of human-object interaction","author":"yu","year":"2014","journal-title":"ACCV"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.342"},{"key":"ref4","article-title":"Co-occurrence feature learning for skeleton based action recognition using regularized deep 1stm networks","author":"zhu","year":"2016","journal-title":"AAAI"},{"key":"ref3","article-title":"Hierarchical recurrent neural network for skeleton based action recognition","author":"du","year":"2015","journal-title":"CVPR"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.115"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.460"},{"key":"ref8","article-title":"Modeling temporal dynamics and spatial configurations of actions using two-stream recurrent neural networks","author":"wang","year":"2017","journal-title":"CVPR"},{"key":"ref7","article-title":"Spatio-temporal 1stm with trust gates for 3d human action recognition","author":"liu","year":"2016","journal-title":"ECCV"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2015.11.019"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2014.04.011"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/2398356.2398381"},{"key":"ref20","article-title":"Online human action detection using joint classification-regression recurrent neural networks","author":"li","year":"2016","journal-title":"ECCV"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"journal-title":"PKU-MMD A Large Scale Benchmark for Continuous Multi-Modal Human Action Understanding","year":"2017","author":"liu","key":"ref21"},{"journal-title":"Improving Neural Networks by Preventing Co-adaptation of Feature Detectors","year":"2012","author":"hinton","key":"ref24"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/78.650093"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298664"}],"event":{"name":"2017 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)","start":{"date-parts":[[2017,7,10]]},"location":"Hong Kong, Hong Kong","end":{"date-parts":[[2017,7,14]]}},"container-title":["2017 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8014334\/8026209\/08026278.pdf?arnumber=8026278","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,2]],"date-time":"2022-08-02T12:15:18Z","timestamp":1659442518000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/8026278\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,7]]},"references-count":25,"URL":"https:\/\/doi.org\/10.1109\/icmew.2017.8026278","relation":{},"subject":[],"published":{"date-parts":[[2017,7]]}}}