{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T22:48:49Z","timestamp":1742942929262,"version":"3.40.3"},"publisher-location":"Cham","reference-count":29,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031500718"},{"type":"electronic","value":"9783031500725"}],"license":[{"start":{"date-parts":[[2023,12,29]],"date-time":"2023-12-29T00:00:00Z","timestamp":1703808000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,12,29]],"date-time":"2023-12-29T00:00:00Z","timestamp":1703808000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-50072-5_6","type":"book-chapter","created":{"date-parts":[[2023,12,28]],"date-time":"2023-12-28T08:02:17Z","timestamp":1703750537000},"page":"70-82","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["An Adaptive-Guidance GAN for\u00a0Accurate Face Reenactment"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2278-1955","authenticated-orcid":false,"given":"Xiaoyu","family":"Chai","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1376-0167","authenticated-orcid":false,"given":"Jun","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3107-1664","authenticated-orcid":false,"given":"Dongshu","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6297-7138","authenticated-orcid":false,"given":"Hongdou","family":"Yao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,12,29]]},"reference":[{"key":"6_CR1","doi-asserted-by":"publisher","first-page":"2998","DOI":"10.1109\/TMM.2021.3068567","volume":"23","author":"X Chai","year":"2021","unstructured":"Chai, X., Chen, J., Liang, C., Xu, D., Lin, C.: Expression-aware face reconstruction via a dual-stream network. IEEE Trans. Multimedia 23, 2998\u20133012 (2021)","journal-title":"IEEE Trans. Multimedia"},{"key":"6_CR2","doi-asserted-by":"publisher","first-page":"7991","DOI":"10.1109\/TII.2021.3064369","volume":"17","author":"MN Cheema","year":"2021","unstructured":"Cheema, M.N., et al.: Modified GAN-cAED to minimize risk of unintentional liver major vessels cutting by controlled segmentation using CTA\/SPET-CT. IEEE Trans. Ind. Inform. 17, 7991\u20138002 (2021)","journal-title":"IEEE Trans. Ind. Inform."},{"key":"6_CR3","doi-asserted-by":"crossref","unstructured":"Deng, J., Guo, J., Xue, N., Zafeiriou, S.: Arcface: additive angular margin loss for deep face recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4690\u20134699 (2019)","DOI":"10.1109\/CVPR.2019.00482"},{"issue":"5","key":"6_CR4","doi-asserted-by":"publisher","first-page":"807","DOI":"10.1016\/j.imavis.2009.08.002","volume":"28","author":"R Gross","year":"2010","unstructured":"Gross, R., Matthews, I., Cohn, J., Kanade, T., Baker, S.: Multi-pie. Image Vision Comput. 28(5), 807\u2013813 (2010)","journal-title":"Image Vision Comput."},{"key":"6_CR5","doi-asserted-by":"crossref","unstructured":"Ha, S., Kersner, M., Kim, B., Seo, S., Kim, D.: Marionette: few-shot face reenactment preserving identity of unseen targets. In: Proceedings of the AAAI Conference on Artificial Intelligence, pp. 10893\u201310900 (2020)","DOI":"10.1609\/aaai.v34i07.6721"},{"issue":"11","key":"6_CR6","doi-asserted-by":"publisher","first-page":"5464","DOI":"10.1109\/TIP.2019.2916751","volume":"28","author":"Z He","year":"2019","unstructured":"He, Z., Zuo, W., Kan, M., Shan, S., Chen, X.: AttGAN: facial attribute editing by only changing what you want. IEEE Trans. Image Process. 28(11), 5464\u20135478 (2019)","journal-title":"IEEE Trans. Image Process."},{"key":"6_CR7","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. In: International Conference on Learning Representations, pp. 1\u201315 (2015)"},{"key":"6_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"299","DOI":"10.1007\/978-3-030-58621-8_18","volume-title":"Computer Vision \u2013 ECCV 2020","author":"M Kowalski","year":"2020","unstructured":"Kowalski, M., Garbin, S.J., Estellers, V., Baltru\u0161aitis, T., Johnson, M., Shotton, J.: CONFIG: controllable neural face image generation. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12356, pp. 299\u2013315. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58621-8_18"},{"key":"6_CR9","doi-asserted-by":"crossref","unstructured":"Lee, C., Liu, Z., Wu, L., Luo, P.: MaskGAN: towards diverse and interactive facial image manipulation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5549\u20135558 (2020)","DOI":"10.1109\/CVPR42600.2020.00559"},{"key":"6_CR10","doi-asserted-by":"crossref","unstructured":"Liu, M., et al.: STGAN: a unified selective transfer network for arbitrary image attribute editing. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3673\u20133682 (2019)","DOI":"10.1109\/CVPR.2019.00379"},{"key":"6_CR11","doi-asserted-by":"crossref","unstructured":"Nagrani, A., Chung, J.S., Zisserman, A.: VoxCeleb: a large-scale speaker identification dataset. In: Proceedings of the Annual Conference of the International Speech Communication Association, pp. 2616\u20132620 (2017)","DOI":"10.21437\/Interspeech.2017-950"},{"key":"6_CR12","doi-asserted-by":"crossref","unstructured":"Ren, Y., Li, G., Chen, Y., Li, T.H., Liu, S.: PIRenderer: controllable portrait image generation via semantic neural rendering. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 13759\u201313768 (2021)","DOI":"10.1109\/ICCV48922.2021.01350"},{"key":"6_CR13","doi-asserted-by":"crossref","unstructured":"Shen, Y., Luo, P., Yan, J., Wang, X., Tang, X.: FaceID-GAN: learning a symmetry three-player GAN for identity-preserving face synthesis. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 821\u2013830 (2018)","DOI":"10.1109\/CVPR.2018.00092"},{"key":"6_CR14","doi-asserted-by":"crossref","unstructured":"Siarohin, A., Lathuili\u00e8re, S., Tulyakov, S., Ricci, E., Sebe, N.: Animating arbitrary objects via deep motion transfer. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2377\u20132386 (2019)","DOI":"10.1109\/CVPR.2019.00248"},{"key":"6_CR15","unstructured":"Siarohin, A., Lathuili\u00e8re, S., Tulyakov, S., Ricci, E., Sebe, N.: First order motion model for image animation. In: Advances in Neural Information Processing Systems 32, pp. 7137\u20137147 (2019)"},{"key":"6_CR16","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. In: International Conference on Learning Representations, pp. 1\u201314 (2014)"},{"issue":"1","key":"6_CR17","first-page":"157","volume":"43","author":"L Tran","year":"2019","unstructured":"Tran, L., Liu, X.: On learning 3D face morphable model from in-the-wild images. IEEE Trans. Pattern Anal. Mach. Intell. 43(1), 157\u2013171 (2019)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"6_CR18","doi-asserted-by":"publisher","first-page":"2009","DOI":"10.1007\/s00371-021-02262-8","volume":"38","author":"L Wang","year":"2022","unstructured":"Wang, L., Sun, Y., Wang, Z.: CCS-GAN: a semi-supervised generative adversarial network for image classification. Vis. Comput. 38, 2009\u20132021 (2022)","journal-title":"Vis. Comput."},{"key":"6_CR19","doi-asserted-by":"publisher","first-page":"6142","DOI":"10.1109\/TIP.2021.3092814","volume":"30","author":"Y Wen","year":"2021","unstructured":"Wen, Y., et al.: Structure-aware motion deblurring using multi-adversarial optimized CycleGAN. IEEE Trans. Image Process. 30, 6142\u20136155 (2021)","journal-title":"IEEE Trans. Image Process."},{"key":"6_CR20","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"690","DOI":"10.1007\/978-3-030-01261-8_41","volume-title":"Computer Vision \u2013 ECCV 2018","author":"O Wiles","year":"2018","unstructured":"Wiles, O., Koepke, A.S., Zisserman, A.: X2Face: a network for controlling face generation using images, audio, and pose codes. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11217, pp. 690\u2013706. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01261-8_41"},{"key":"6_CR21","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"622","DOI":"10.1007\/978-3-030-01246-5_37","volume-title":"Computer Vision \u2013 ECCV 2018","author":"W Wu","year":"2018","unstructured":"Wu, W., Zhang, Y., Li, C., Qian, C., Loy, C.C.: ReenactGAN: learning to reenact faces via boundary transfer. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11205, pp. 622\u2013638. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01246-5_37"},{"issue":"11","key":"6_CR22","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. Foren. Secur. 13(11), 2884\u20132896 (2018)","journal-title":"IEEE Trans. Inf. Foren. Secur."},{"key":"6_CR23","doi-asserted-by":"crossref","unstructured":"Zakharov, E., Shysheya, A., Burkov, E., Lempitsky, V.: Few-shot adversarial learning of realistic neural talking head models. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 9459\u20139468 (2019)","DOI":"10.1109\/ICCV.2019.00955"},{"key":"6_CR24","doi-asserted-by":"crossref","unstructured":"Zeng, X., Pan, Y., Wang, M., Zhang, J., Liu, Y.: Realistic face reenactment via self-supervised disentangling of identity and pose. In: Proceedings of the AAAI Conference on Artificial Intelligence, pp. 12757\u201312764 (2020)","DOI":"10.1609\/aaai.v34i07.6970"},{"key":"6_CR25","first-page":"1283","volume":"39","author":"Y Zhang","year":"2023","unstructured":"Zhang, Y., Han, S., Zhang, Z., Wang, J., Bi, H.: CF-GAN: cross-domain feature fusion generative adversarial network for text-to-image synthesis. Vis. Comput. 39, 1283\u20131293 (2023)","journal-title":"Vis. Comput."},{"key":"6_CR26","unstructured":"Zhao, J., et al.: Dual-agent GANs for photorealistic and identity preserving profile face synthesis. In: Advances in Neural Information Processing Systems 30 (2017)"},{"key":"6_CR27","doi-asserted-by":"crossref","unstructured":"Zhou, Y., Deng, J., Kotsia, I., Zafeiriou, S.: Dense 3D face decoding over 2500fps: joint texture & shape convolutional mesh decoders. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1097\u20131106 (2019)","DOI":"10.1109\/CVPR.2019.00119"},{"key":"6_CR28","doi-asserted-by":"crossref","unstructured":"Zhu, J., Park, T., Isola, P., Efros, A.A.: Unpaired image-to-image translation using cycle-consistent adversarial networks. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2223\u20132232 (2017)","DOI":"10.1109\/ICCV.2017.244"},{"key":"6_CR29","doi-asserted-by":"crossref","unstructured":"Zhu, P., Abdal, R., Qin, Y., Wonka, P.: SEAN: image synthesis with semantic region-adaptive normalization. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5104\u20135113 (2020)","DOI":"10.1109\/CVPR42600.2020.00515"}],"container-title":["Lecture Notes in Computer Science","Advances in Computer Graphics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-50072-5_6","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,28]],"date-time":"2023-12-28T08:03:32Z","timestamp":1703750612000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-50072-5_6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,29]]},"ISBN":["9783031500718","9783031500725"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-50072-5_6","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023,12,29]]},"assertion":[{"value":"29 December 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CGI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Computer Graphics International Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shanghai","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 August 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1 September 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cgi2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"385","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"149","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"39% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}