{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,4]],"date-time":"2024-08-04T00:16:45Z","timestamp":1722730605759},"reference-count":13,"publisher":"Institute of Electronics, Information and Communications Engineers (IEICE)","issue":"8","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEICE Trans. Fundamentals"],"published-print":{"date-parts":[[2024,8,1]]},"DOI":"10.1587\/transfun.2024eal2004","type":"journal-article","created":{"date-parts":[[2024,3,17]],"date-time":"2024-03-17T22:15:24Z","timestamp":1710713724000},"page":"1435-1439","source":"Crossref","is-referenced-by-count":0,"title":["A Dual-Branch Algorithm for Semantic-Focused Face Super-Resolution Reconstruction"],"prefix":"10.1587","volume":"E107.A","author":[{"given":"Qi","family":"QI","sequence":"first","affiliation":[{"name":"Department of Decision Consulting, Party School of Liaoning Provincial Party Committee"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liuyi","family":"MENG","sequence":"additional","affiliation":[{"name":"School of Robotics Science and Engineering, Northeastern University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ming","family":"XU","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Shenyang University of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bing","family":"BAI","sequence":"additional","affiliation":[{"name":"Department of Leadership Science, Party School of Liaoning Provincial Party Committee"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"532","reference":[{"key":"1","doi-asserted-by":"publisher","unstructured":"[1] C. Chen, D. Gong, H. Wang, Z. Li, and K.-Y.K. Wong, \u201cLearning spatial attention for face super-resolution,\u201d IEEE Trans. Image Process., vol.30, pp.1219-1231, 2021. 10.1109\/tip.2020.3043093","DOI":"10.1109\/TIP.2020.3043093"},{"key":"2","unstructured":"[2] I. Goodfellow, J. Pouget-Abadie, M. Mirza, et al., \u201cGenerative adversarial nets,\u201d Advances in Neural Information Processing Systems, 27, 2014."},{"key":"3","doi-asserted-by":"crossref","unstructured":"[3] S. Menon, A. Damian, S. Hu, N. Ravi, and C. Rudin, \u201cPulse: Self-supervised photo upsampling via latent space exploration of generative models,\u201d Proc. IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp.2437-2445, 2020. 10.1109\/cvpr42600.2020.00251","DOI":"10.1109\/CVPR42600.2020.00251"},{"key":"4","doi-asserted-by":"crossref","unstructured":"[4] C. Ma, Z. Jiang, Y. Rao, J. Lu, and J. Zhou, \u201cDeep face super-resolution with iterative collaboration between attentive recovery and landmark estimation,\u201d Proc. IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp.5569-5578, 2020. 10.1109\/cvpr42600.2020.00561","DOI":"10.1109\/CVPR42600.2020.00561"},{"key":"5","doi-asserted-by":"crossref","unstructured":"[5] X. Wang, Y. Li, H. Zhang, and Y. Shan, \u201cTowards real-world blind face restoration with generative facial prior,\u201d Proc. IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp.9168-9178, 2021. 10.1109\/cvpr46437.2021.00905","DOI":"10.1109\/CVPR46437.2021.00905"},{"key":"6","doi-asserted-by":"crossref","unstructured":"[6] C. Ledig, L. Theis, F. Husz\u00e1r, J. Caballero, A. Cunningham, A. Acosta, A. Aitken, A. Tejani, J. Totz, Z. Wang, and W. Shi, \u201cPhoto-realistic single image super resolution using a generative adversarial network,\u201d Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp.4681-4690, 2017. 10.1109\/CVPR.2017.19","DOI":"10.1109\/CVPR.2017.19"},{"key":"7","doi-asserted-by":"crossref","unstructured":"[7] C. Yu, J. Wang, C. Peng, C. Gao, G. Yu, and N. Sang, \u201cBiSeNet: Bilateral segmentation network for real-time semantic segmentation,\u201d Proc. European Conference on Computer Vision, pp.325-341, 2018. 10.1007\/978-3-030-01261-8_20","DOI":"10.1007\/978-3-030-01261-8_20"},{"key":"8","doi-asserted-by":"crossref","unstructured":"[8] Z. Liu, P. Luo, X. Wang, and X. Tang, \u201cDeep learning face attributes in the wild,\u201d Proc. IEEE International Conference on Computer Vision, pp.3730-3738, 2015. 10.1109\/iccv.2015.425","DOI":"10.1109\/ICCV.2015.425"},{"key":"9","doi-asserted-by":"crossref","unstructured":"[9] V. Le, J. Brandt, L. Zhe, L.D. Bourdev, and T.S. Huang, \u201cInteractive facial feature localization,\u201d Proc. European Conference on Computer Vision, pp.679-692, 2012. 10.1007\/978-3-642-33712-3_49","DOI":"10.1007\/978-3-642-33712-3_49"},{"key":"10","doi-asserted-by":"crossref","unstructured":"[10] T. Karras, S. Laine, and T. Aila, \u201cA style-based generator architecture for generative adversarial networks,\u201d Proc. IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp.4396-4405, 2019. 10.1109\/cvpr.2019.00453","DOI":"10.1109\/CVPR.2019.00453"},{"key":"11","doi-asserted-by":"publisher","unstructured":"[11] C. Liu, \u201cGabor-based kernel PCA with fractional power polynomial models for face recognition,\u201d IEEE Trans. Pattern Anal. Mach. Intell., vol.26, no.5, pp.572-581, 2004. 10.1109\/tpami.2004.1273927","DOI":"10.1109\/TPAMI.2004.1273927"},{"key":"12","doi-asserted-by":"crossref","unstructured":"[12] X. Wang, R. Girshick, A. Gupta, and K. He, \u201cNon-local neural networks,\u201d Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp.7794-7803, 2018. 10.1109\/cvpr.2018.00813","DOI":"10.1109\/CVPR.2018.00813"},{"key":"13","doi-asserted-by":"crossref","unstructured":"[13] Q. Cao, L. Shen, W. Xie, O.M. Parkhi, and A. Zisserman, \u201cVGGFace2: A dataset for recognising faces across pose and age,\u201d 2018 13th IEEE International Conference on Automatic Face &amp; Gesture Recognition (FG 2018), pp.67-74, 2018. 10.1109\/fg.2018.00020","DOI":"10.1109\/FG.2018.00020"}],"container-title":["IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transfun\/E107.A\/8\/E107.A_2024EAL2004\/_pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,3]],"date-time":"2024-08-03T03:30:01Z","timestamp":1722655801000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transfun\/E107.A\/8\/E107.A_2024EAL2004\/_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,1]]},"references-count":13,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2024]]}},"URL":"https:\/\/doi.org\/10.1587\/transfun.2024eal2004","relation":{},"ISSN":["0916-8508","1745-1337"],"issn-type":[{"type":"print","value":"0916-8508"},{"type":"electronic","value":"1745-1337"}],"subject":[],"published":{"date-parts":[[2024,8,1]]},"article-number":"2024EAL2004"}}