{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T15:13:47Z","timestamp":1768749227920,"version":"3.49.0"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2022,12,16]],"date-time":"2022-12-16T00:00:00Z","timestamp":1671148800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,12,16]],"date-time":"2022-12-16T00:00:00Z","timestamp":1671148800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61876099"],"award-info":[{"award-number":["61876099"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Key RD Program of China","award":["2019YFB1311001"],"award-info":[{"award-number":["2019YFB1311001"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["SIViP"],"published-print":{"date-parts":[[2023,7]]},"DOI":"10.1007\/s11760-022-02409-7","type":"journal-article","created":{"date-parts":[[2022,12,16]],"date-time":"2022-12-16T08:03:55Z","timestamp":1671177835000},"page":"1965-1973","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Face frontalization with deep GAN via multi-attention mechanism"],"prefix":"10.1007","volume":"17","author":[{"given":"Jiaqian","family":"Cao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenxue","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yujiao","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luna","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiyang","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,12,16]]},"reference":[{"key":"2409_CR1","doi-asserted-by":"crossref","unstructured":"Parkhi, O.M., Vedaldi, A., Zisserman, A.: Deep face recognition. In: British Machine Vision Conference (2015)","DOI":"10.5244\/C.29.41"},{"key":"2409_CR2","doi-asserted-by":"crossref","unstructured":"Sun, Y., Wang, X., Tang, X.: Deep learning face representation from predicting 10,000 classes. In: 2014 IEEE Conference on Computer Vision and Pattern Recognition, pp. 1891\u20131898 (2014)","DOI":"10.1109\/CVPR.2014.244"},{"key":"2409_CR3","doi-asserted-by":"crossref","unstructured":"Schroff, F., Kalenichenko, D., Philbin, J.: Facenet: a unified embedding for face recognition and clustering. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 815\u2013823 (2015)","DOI":"10.1109\/CVPR.2015.7298682"},{"key":"2409_CR4","doi-asserted-by":"crossref","unstructured":"Cao, K., Rong, Y., Li, C., Tang, X., Loy, C.C.: Pose-robust face recognition via deep residual equivariant mapping. In: 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5187\u20135196 (2018)","DOI":"10.1109\/CVPR.2018.00544"},{"key":"2409_CR5","doi-asserted-by":"crossref","unstructured":"Hu, Y., Wu, X., Yu, B., He, R., Sun, Z.: Pose-guided photorealistic face rotation. In: 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 8398\u20138406 (2018)","DOI":"10.1109\/CVPR.2018.00876"},{"key":"2409_CR6","unstructured":"Yim, J., Jung, H., Yoo, B.I., Choi, C., Kim, J.: Rotating your face using multi-task deep neural network. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2015)"},{"key":"2409_CR7","unstructured":"Zhu, Z., Luo, P., Wang, X., Tang, X.: Multi-view perceptron: a deep model for learning face identity and view representations. In: Advances in Neural Information Processing Systems (2014)"},{"key":"2409_CR8","doi-asserted-by":"crossref","unstructured":"Cole, F., Belanger, D., Krishnan, D., Sarna, A., Mosseri, I., Freeman, W.T.: Synthesizing normalized faces from facial identity features. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3386\u20133395 (2017)","DOI":"10.1109\/CVPR.2017.361"},{"key":"2409_CR9","unstructured":"Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., WardeFarley, D., Ozair, S., Courville, A., Bengio, Y.: Generative adversarial nets. In: Neural Information Processing Systems (2014)"},{"key":"2409_CR10","doi-asserted-by":"crossref","unstructured":"Huang, R., Zhang, S., Li, T., He, R.: Beyond face rotation: Global and local perception gan for photorealistic and identity preserving frontal view synthesis. In: 2017 IEEE International Conference on Computer Vision (ICCV), pp. 2458\u20132467 (2017)","DOI":"10.1109\/ICCV.2017.267"},{"key":"2409_CR11","doi-asserted-by":"crossref","unstructured":"Tran, L., Yin, X., Liu, X.: Disentangled representation learning gan for pose-invariant face recognition. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1283\u20131292 (2017)","DOI":"10.1109\/CVPR.2017.141"},{"key":"2409_CR12","doi-asserted-by":"crossref","unstructured":"Li, P., Wu, X., Hu, Y., He, R., Sun, Z.: M2fpa: a multi-yaw multi-pitch high-quality dataset and benchmark for facial pose analysis. In: 2019 IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 10 042\u201310 050 (2019)","DOI":"10.1109\/ICCV.2019.01014"},{"key":"2409_CR13","doi-asserted-by":"crossref","unstructured":"Yin, Y, Jiang, S., Robinson, J.P., Fu, Y.: Dual-attention gan for large-pose face frontalization. In: 2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020), pp. 249\u2013256 (2020)","DOI":"10.1109\/FG47880.2020.00004"},{"key":"2409_CR14","doi-asserted-by":"publisher","first-page":"104676","DOI":"10.1109\/ACCESS.2020.2996637","volume":"8","author":"X Luan","year":"2020","unstructured":"Luan, X., Geng, H., Liu, L., Li, W., Zhao, Y., Ren, M.: Geometry structure preserving based gan for multi-pose face frontalization and recognition. IEEE Access 8, 104676\u2013104687 (2020)","journal-title":"IEEE Access"},{"key":"2409_CR15","doi-asserted-by":"publisher","first-page":"909","DOI":"10.1109\/TIFS.2020.3025412","volume":"16","author":"Z Zhang","year":"2021","unstructured":"Zhang, Z., Liang, R., Chen, X., Xu, X., Hu, G., Zuo, W., Hancock, E.R.: Semi-supervised face frontalization in the wild. IEEE Trans. Inf. Forensics Secur. 16, 909\u2013922 (2021)","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"2409_CR16","doi-asserted-by":"crossref","unstructured":"Luo, H., Cen, S., Ding, Q., Chen, X.: Frontal face reconstructionbased on detail identification, variable scale self-attention and flexible skip connection. In: Neural Computing & Applications (2022)","DOI":"10.1007\/s00521-022-07124-5"},{"key":"2409_CR17","doi-asserted-by":"crossref","unstructured":"Qian, Y., Deng, W., Hu, J.: Unsupervised face normalization with extreme pose and expression in the wild. In: 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 9843\u20139850 (2019)","DOI":"10.1109\/CVPR.2019.01008"},{"key":"2409_CR18","doi-asserted-by":"crossref","unstructured":"Zhao, J., Cheng, Y., Xu, Y., Xiong, L., Li, J., Zhao, F., Jayashree, K., Pranata, S., Shen, S., Xing, J., Yan, S., Feng, J.: Towards pose invariant face recognition in the wild. In: 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2207\u20132216 (2018)","DOI":"10.1109\/CVPR.2018.00235"},{"key":"2409_CR19","doi-asserted-by":"crossref","unstructured":"Woo, S., Park, J., Lee, J.-Y., Kweon, I.S.: Cbam: convolutional block attention module. In: Computer Vision\u2014ECCV 2018, pp. 3\u201319 (2018)","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"2409_CR20","unstructured":"Mejjati, Y.A., Richardt, C., Tompkin, J., Cosker, D., Kim, K.I.: Unsupervised attention-guided image to image translation. In: Proceedings of the 32nd International Conference on Neural Information Processing Systems, pp. 3697\u20133707 (2018)"},{"key":"2409_CR21","doi-asserted-by":"crossref","unstructured":"Fu, J., Liu, J., Tian, H., Li, Y., Bao, Y., Fang, Z., Lu, H.: Dual attention network for scene segmentation. In: 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3141\u20133149 (2019)","DOI":"10.1109\/CVPR.2019.00326"},{"key":"2409_CR22","unstructured":"Zhang, H., Goodfellow, I., Metaxas, D., Odena, A.: Self-attention generative adversarial networks (2018)"},{"key":"2409_CR23","unstructured":"Denton, E., Chintala, S., Szlam, A., Fergus, R.: Deep generative image models using a laplacian pyramid of adversarial networks. In: International Conference on Neural Information Processing Systems, pp. 1486\u20131494 (2015)"},{"key":"2409_CR24","unstructured":"Radford, A., Metz, L., Chintala, S.: Unsupervised representation learning with deep convolutional generative adversarial networks. Computer Science (2015)"},{"key":"2409_CR25","unstructured":"Arjovsky, M., Chintala, S., Bottou, L.: Wasserstein generative adversarial networks. In: Proceedings of the 34th International Conference on Machine Learning (ICML), pp. 214\u2013223 (2017)"},{"key":"2409_CR26","unstructured":"Gulrajani, I., Ahmed, F., Arjovsky, M., Dumoulin, V., Courville, A.: Improved training of wasserstein gans, pp. 5767\u20135777 (2017)"},{"key":"2409_CR27","unstructured":"Berthelot, D., Schumm, T., Metz, L.: Began: boundary equilibrium generative adversarial networks. arXiv (2017)"},{"key":"2409_CR28","doi-asserted-by":"crossref","unstructured":"Hassner, T., Harel, S., Paz, E., Enbar, R.: Effective face frontalization in unconstrained images. In: Computer Vision Pattern Recognition, pp. 4295\u20134304 (2015)","DOI":"10.1109\/CVPR.2015.7299058"},{"key":"2409_CR29","doi-asserted-by":"crossref","unstructured":"Zhu, X., Lei, Z., Yan, J., Yi, D., Li, S.Z.: High-fidelity pose and expression normalization for face recognition in the wild. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 787\u2013796 (2015)","DOI":"10.1109\/CVPR.2015.7298679"},{"key":"2409_CR30","doi-asserted-by":"publisher","first-page":"77872","DOI":"10.1109\/ACCESS.2022.3193386","volume":"10","author":"S Cen","year":"2022","unstructured":"Cen, S., Luo, H., Huang, J., Shi, W., Chen, X.: Pre-trained feature fusion and multidomain identification generative adversarial network for face frontalization. IEEE Access 10, 77872\u201377882 (2022)","journal-title":"IEEE Access"},{"key":"2409_CR31","first-page":"2204","volume":"3","author":"V Mnih","year":"2014","unstructured":"Mnih, V., Heess, N., Graves, A., Kavukcuoglu, K.: Recurrent models of visual attention. Adv. Neural Inf. Process. Syst. 3, 2204\u20132212 (2014)","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"2409_CR32","unstructured":"Bahdanau, D., Cho, K., Bengio, Y.: Neural machine translation by jointly learning to align and translate. Computer Science (2014)"},{"key":"2409_CR33","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, L., Polosukhin, I.: Attention is all you need. arXiv (2017)"},{"key":"2409_CR34","doi-asserted-by":"publisher","first-page":"1218","DOI":"10.1109\/TIFS.2020.3031386","volume":"16","author":"S Duan","year":"2021","unstructured":"Duan, S., Chen, Z., Wu, Q., Cai, L., Lu, D.: Multi-scale gradients self-attention residual learning for face photo-sketch transformation. IEEE Trans. Inf. Forensics Secur. 16, 1218\u20131230 (2021)","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"2409_CR35","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"issue":"11","key":"2409_CR36","doi-asserted-by":"publisher","first-page":"2884","DOI":"10.1109\/TIFS.2018.2833032","volume":"13","author":"X Wu","year":"2018","unstructured":"Wu, X., He, R., Sun, Z., Tan, T.: A light cnn for deep face representation with noisy labels. IEEE Trans. Inf. Forensics Secur. 13(11), 2884\u20132896 (2018)","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"2409_CR37","doi-asserted-by":"crossref","unstructured":"Johnson, J., Alahi, A., Fei-Fei, L.: Perceptual losses for real-time style transfer and super-resolution. In: Computer Vision\u2014ECCV 2016, pp. 694\u2013711 (2016)","DOI":"10.1007\/978-3-319-46475-6_43"},{"key":"2409_CR38","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. Computer Science (2014)"},{"issue":"1","key":"2409_CR39","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1109\/TSMCA.2007.909557","volume":"38","author":"W Gao","year":"2008","unstructured":"Gao, W., Cao, B., Shan, S., Chen, X., Zhou, D., Zhang, X., Zhao, D.: The cas-peal large-scale Chinese face database and baseline evaluations. IEEE Trans. Syst. Man Cybern. Part A Syst. Hum. 38(1), 149\u2013161 (2008)","journal-title":"IEEE Trans. Syst. Man Cybern. Part A Syst. Hum."},{"key":"2409_CR40","unstructured":"\u201cCasia-facev5\u201d http:\/\/biometrics.idealtest.org\/"},{"key":"2409_CR41","doi-asserted-by":"publisher","unstructured":"Deng, J., Guo, J., Ververas, E., Kotsia, I., Zafeiriou, S.: RetinaFace: single-shot multi-level face localisation in the wild. In: 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5202\u20135211 (2020).https:\/\/doi.org\/10.1109\/CVPR42600.2020.00525","DOI":"10.1109\/CVPR42600.2020.00525"},{"key":"2409_CR42","doi-asserted-by":"publisher","first-page":"103526","DOI":"10.1016\/j.cviu.2022.103526","volume":"222","author":"Y Liu","year":"2022","unstructured":"Liu, Y., Chen, J.: Unsupervised face frontalization using disentangled representation-learning CycleGAN. Comput. Vis. Image Underst. 222, 103526 (2022)","journal-title":"Comput. Vis. Image Underst."}],"container-title":["Signal, Image and Video Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-022-02409-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11760-022-02409-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-022-02409-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,10]],"date-time":"2024-10-10T15:04:07Z","timestamp":1728572647000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11760-022-02409-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,16]]},"references-count":42,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2023,7]]}},"alternative-id":["2409"],"URL":"https:\/\/doi.org\/10.1007\/s11760-022-02409-7","relation":{},"ISSN":["1863-1703","1863-1711"],"issn-type":[{"value":"1863-1703","type":"print"},{"value":"1863-1711","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12,16]]},"assertion":[{"value":"23 July 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 November 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 November 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 December 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}