{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,5,14]],"date-time":"2024-05-14T00:26:22Z","timestamp":1715646382128},"reference-count":9,"publisher":"Institute of Electronics, Information and Communications Engineers (IEICE)","issue":"8","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEICE Trans. Inf. & Syst."],"published-print":{"date-parts":[[2023,8,1]]},"DOI":"10.1587\/transinf.2023edl8001","type":"journal-article","created":{"date-parts":[[2023,7,31]],"date-time":"2023-07-31T22:18:31Z","timestamp":1690841911000},"page":"1292-1295","source":"Crossref","is-referenced-by-count":0,"title":["Temporal-Based Action Clustering for Motion Tendencies"],"prefix":"10.1587","volume":"E106.D","author":[{"given":"Xingyu","family":"QIAN","sequence":"first","affiliation":[{"name":"Chinese Acad Sci, Shanghai Institute of Microsystem and Information Technology"},{"name":"Shanghaitech University"}]},{"given":"Xiaogang","family":"CHEN","sequence":"additional","affiliation":[{"name":"Chinese Acad Sci, Shanghai Institute of Microsystem and Information Technology"}]},{"given":"Aximu","family":"YUEMAIER","sequence":"additional","affiliation":[{"name":"Chinese Acad Sci, Shanghai Institute of Microsystem and Information Technology"},{"name":"Shanghaitech University"}]},{"given":"Shunfen","family":"LI","sequence":"additional","affiliation":[{"name":"Chinese Acad Sci, Shanghai Institute of Microsystem and Information Technology"}]},{"given":"Weibang","family":"DAI","sequence":"additional","affiliation":[{"name":"Chinese Acad Sci, Shanghai Institute of Microsystem and Information Technology"}]},{"given":"Zhitang","family":"SONG","sequence":"additional","affiliation":[{"name":"Chinese Acad Sci, Shanghai Institute of Microsystem and Information Technology"}]}],"member":"532","reference":[{"key":"1","doi-asserted-by":"crossref","unstructured":"[1] J. Bock, R. Krajewski, T. Moers, S. Runde, L. Vater, and L. Eckstein, \u201cThe ind dataset: A drone dataset of naturalistic road user trajectories at german intersections,\u201d 2020 IEEE Intelligent Vehicles Symposium (IV), pp.1929-1934, 2020. 10.1109\/iv47402.2020.9304839","DOI":"10.1109\/IV47402.2020.9304839"},{"key":"2","unstructured":"[2] X. Qian, A. Yuemaier, L. Liang, W.-C. Yang, X. Chen, S. Li, W. Dai, and Z. Song, \u201cMemory-like adaptive modeling multi-agent learning system,\u201d arXiv e-prints, arXiv:2212.07646, Dec. 2022."},{"key":"3","doi-asserted-by":"crossref","unstructured":"[3] C. Feichtenhofer, A. Pinz, and A. Zisserman, \u201cConvolutional two-stream network fusion for video action recognition,\u201d 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.1933-1941, 2016. 10.1109\/cvpr.2016.213","DOI":"10.1109\/CVPR.2016.213"},{"key":"4","doi-asserted-by":"crossref","unstructured":"[4] D. Tran, L. Bourdev, R. Fergus, L. Torresani, and M. Paluri, \u201cLearning spatiotemporal features with 3d convolutional networks,\u201d 2015 IEEE ICCV, pp.4489-4497, 2015. 10.1109\/iccv.2015.510","DOI":"10.1109\/ICCV.2015.510"},{"key":"5","doi-asserted-by":"crossref","unstructured":"[5] T. Han, W. Xie, and A. Zisserman, \u201cVideo representation learning by dense predictive coding,\u201d 2019 IEEE\/CVF ICCVW, pp.1483-1492, 2019. 10.1109\/iccvw.2019.00186","DOI":"10.1109\/ICCVW.2019.00186"},{"key":"6","doi-asserted-by":"crossref","unstructured":"[6] J. Wang, J. Jiao, L. Bao, S. He, Y. Liu, and W. Liu, \u201cSelf-supervised spatio-temporal representation learning for videos by predicting motion and appearance statistics,\u201d 2019 IEEE\/CVF CVPR, pp.4001-4010, June 2019. 10.1109\/cvpr.2019.00413","DOI":"10.1109\/CVPR.2019.00413"},{"key":"7","doi-asserted-by":"crossref","unstructured":"[7] C. Zhuang, T. She, A. Andonian, M.S. Mark, and D. Yamins, \u201cUnsupervised learning from video with deep neural embeddings,\u201d 2020 IEEE\/CVF CVPR, pp.9560-9569, 2020. 10.1109\/cvpr42600.2020.00958","DOI":"10.1109\/CVPR42600.2020.00958"},{"key":"8","doi-asserted-by":"publisher","unstructured":"[8] H. Wang, A. Kl\u00e4ser, C. Schmid, and C.-L. Liu, \u201cDense trajectories and motion boundary descriptors for action recognition,\u201d IJCV, vol.103, no.1, pp.60-79, 2013. 10.1007\/s11263-012-0594-8","DOI":"10.1007\/s11263-012-0594-8"},{"key":"9","doi-asserted-by":"crossref","unstructured":"[9] S. Casas, A. Sadat, and R. Urtasun, \u201cMp3: A unified model to map, perceive, predict and plan,\u201d 2021 IEEE\/CVF CVPR, pp.14398-14407, 2021. 10.1109\/cvpr46437.2021.01417","DOI":"10.1109\/CVPR46437.2021.01417"}],"container-title":["IEICE Transactions on Information and Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E106.D\/8\/E106.D_2023EDL8001\/_pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T04:58:24Z","timestamp":1715576304000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E106.D\/8\/E106.D_2023EDL8001\/_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,1]]},"references-count":9,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2023]]}},"URL":"https:\/\/doi.org\/10.1587\/transinf.2023edl8001","relation":{},"ISSN":["0916-8532","1745-1361"],"issn-type":[{"value":"0916-8532","type":"print"},{"value":"1745-1361","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,8,1]]},"article-number":"2023EDL8001"}}