{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,12,8]],"date-time":"2024-12-08T05:04:00Z","timestamp":1733634240990,"version":"3.30.1"},"reference-count":8,"publisher":"Institute of Electronics, Information and Communications Engineers (IEICE)","issue":"12","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEICE Trans. Inf. &amp; Syst."],"published-print":{"date-parts":[[2024,12,1]]},"DOI":"10.1587\/transinf.2024edl8041","type":"journal-article","created":{"date-parts":[[2024,7,28]],"date-time":"2024-07-28T22:10:26Z","timestamp":1722204626000},"page":"1550-1553","source":"Crossref","is-referenced-by-count":0,"title":["Temporal Correlation-Based End-to-End Rate Control in DCVC"],"prefix":"10.1587","volume":"E107.D","author":[{"given":"Zhenglong","family":"YANG","sequence":"first","affiliation":[{"name":"School of Urban Rail Transportation, Shanghai University of Engineering Science"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weihao","family":"DENG","sequence":"additional","affiliation":[{"name":"School of Urban Rail Transportation, Shanghai University of Engineering Science"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guozhong","family":"WANG","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Industry Research Institute, Shanghai University of Engineering Science"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tao","family":"FAN","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Industry Research Institute, Shanghai University of Engineering Science"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yixi","family":"LUO","sequence":"additional","affiliation":[{"name":"School of Urban Rail Transportation, Shanghai University of Engineering Science"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"532","reference":[{"key":"1","doi-asserted-by":"publisher","unstructured":"[1] F. Jiang, W. Tao, S. Liu, J. Ren, X. Guo, and D. Zhao, \u201cAn end-to-end compression framework based on convolutional neural networks,\u201d IEEE Trans. Circuits Syst. Video Technol., vol.28, no.10, pp.3007-3018, 2017. 10.1109\/tcsvt.2017.2734838","DOI":"10.1109\/TCSVT.2017.2734838"},{"key":"2","doi-asserted-by":"crossref","unstructured":"[2] G. Lu, W. Ouyang, D. Xu, X. Zhang, C. Cai, and Z. Gao, \u201cDVC: An end-to-end deep video compression framework,\u201d Proc. IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp.10998-11007, 2019. 10.1109\/cvpr.2019.01126","DOI":"10.1109\/CVPR.2019.01126"},{"key":"3","unstructured":"[3] J. Li, B. Li, and Y. Lu, \u201cDeep contextual video compression,\u201d Adv. Neural Inf. Process. Syst., vol.34, pp.18114-18125, 2021."},{"key":"4","doi-asserted-by":"crossref","unstructured":"[4] E. \u00c7etin, M.A. Y\u0131lmaz, and A.M. Tekalp, \u201cFlexible-rate learned hierarchical bi-directional video compression with motion refinement and frame-level bit allocation,\u201d Proc. 2022 IEEE International Conference on Image Processing (ICIP), pp.1206-1210, 2022. 10.1109\/ICIP46576.2022.9897455","DOI":"10.1109\/ICIP46576.2022.9897455"},{"key":"5","doi-asserted-by":"crossref","unstructured":"[5] Y. Li, X. Chen, J. Li, J. Wen, Y. Han, S. Liu, and X. Xu, \u201cRate control for learned video compression,\u201d Proc. ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.2829-2833, 2022. 10.1109\/icassp43922.2022.9746080","DOI":"10.1109\/ICASSP43922.2022.9746080"},{"key":"6","doi-asserted-by":"publisher","unstructured":"[6] B. Li, H. Li, L. Li, and J. Zhang, \u201c\u03bb domain rate control algorithm for high efficiency video coding,\u201d IEEE Trans. Image Process., vol.23, no.9, pp.3841-3854, 2014. 10.1109\/TIP.2014.2336550","DOI":"10.1109\/TIP.2014.2336550"},{"key":"7","doi-asserted-by":"publisher","unstructured":"[7] T. Xue, B. Chen, J. Wu, D. Wei, and W.T. Freeman, \u201cVideo enhancement with task-oriented flow,\u201d Int. J. Comput. Vis., vol.127, pp.1106-1125, 2019. 10.1007\/s11263-018-01144-2","DOI":"10.1007\/s11263-018-01144-2"},{"key":"8","doi-asserted-by":"publisher","unstructured":"[8] D. Ma, F. Zhang, and D.R. Bull, \u201cBVI-DVC: A training database for deep video compression,\u201d IEEE Trans. Multimed., vol.24, pp.3847-3858, 2021. 10.1109\/tmm.2021.3108943","DOI":"10.1109\/TMM.2021.3108943"}],"container-title":["IEICE Transactions on Information and Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E107.D\/12\/E107.D_2024EDL8041\/_pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,7]],"date-time":"2024-12-07T03:24:41Z","timestamp":1733541881000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E107.D\/12\/E107.D_2024EDL8041\/_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,1]]},"references-count":8,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2024]]}},"URL":"https:\/\/doi.org\/10.1587\/transinf.2024edl8041","relation":{},"ISSN":["0916-8532","1745-1361"],"issn-type":[{"type":"print","value":"0916-8532"},{"type":"electronic","value":"1745-1361"}],"subject":[],"published":{"date-parts":[[2024,12,1]]},"article-number":"2024EDL8041"}}