{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,6]],"date-time":"2026-04-06T10:09:50Z","timestamp":1775470190365,"version":"3.50.1"},"publisher-location":"Cham","reference-count":54,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031197802","type":"print"},{"value":"9783031197819","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-19781-9_38","type":"book-chapter","created":{"date-parts":[[2022,10,22]],"date-time":"2022-10-22T12:12:59Z","timestamp":1666440779000},"page":"661-677","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":35,"title":["StyleSwap: Style-Based Generator Empowers Robust Face Swapping"],"prefix":"10.1007","author":[{"given":"Zhiliang","family":"Xu","sequence":"first","affiliation":[]},{"given":"Hang","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Zhibin","family":"Hong","sequence":"additional","affiliation":[]},{"given":"Ziwei","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Jiaming","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Zhizhi","family":"Guo","sequence":"additional","affiliation":[]},{"given":"Junyu","family":"Han","sequence":"additional","affiliation":[]},{"given":"Jingtuo","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Errui","family":"Ding","sequence":"additional","affiliation":[]},{"given":"Jingdong","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,10,23]]},"reference":[{"key":"38_CR1","doi-asserted-by":"crossref","unstructured":"Abdal, R., Qin, Y., Wonka, P.: Image2StyleGAN: how to embed images into the StyleGAN latent space? In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 4432\u20134441 (2019)","DOI":"10.1109\/ICCV.2019.00453"},{"key":"38_CR2","doi-asserted-by":"crossref","unstructured":"Abdal, R., Qin, Y., Wonka, P.: Image2StyleGAN++: how to edit the embedded images? In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 8296\u20138305 (2020)","DOI":"10.1109\/CVPR42600.2020.00832"},{"key":"38_CR3","doi-asserted-by":"crossref","unstructured":"Alaluf, Y., Patashnik, O., Cohen-Or, D.: Restyle: a residual-based StyleGAN encoder via iterative refinement. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 6711\u20136720 (2021)","DOI":"10.1109\/ICCV48922.2021.00664"},{"key":"38_CR4","doi-asserted-by":"crossref","unstructured":"Bitouk, D., Kumar, N., Dhillon, S., Belhumeur, P., Nayar, S.K.: Face swapping: automatically replacing faces in photographs. In: ACM SIGGRAPH 2008 papers, pp. 1\u20138 (2008)","DOI":"10.1145\/1399504.1360638"},{"key":"38_CR5","doi-asserted-by":"crossref","unstructured":"Blanz, V., Scherbaum, K., Vetter, T., Seidel, H.P.: Exchanging faces in images. In: Computer Graphics Forum, vol. 23, pp. 669\u2013676. Wiley Online Library (2004)","DOI":"10.1111\/j.1467-8659.2004.00799.x"},{"key":"38_CR6","doi-asserted-by":"crossref","unstructured":"Burkov, E., Pasechnik, I., Grigorev, A., Lempitsky, V.: Neural head reenactment with latent pose descriptors. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 13786\u201313795 (2020)","DOI":"10.1109\/CVPR42600.2020.01380"},{"key":"38_CR7","doi-asserted-by":"crossref","unstructured":"Chen, R., Chen, X., Ni, B., Ge, Y.: SimSwap: an efficient framework for high fidelity face swapping. In: Proceedings of the 28th ACM International Conference on Multimedia, pp. 2003\u20132011 (2020)","DOI":"10.1145\/3394171.3413630"},{"key":"38_CR8","doi-asserted-by":"crossref","unstructured":"Chung, J.S., Nagrani, A., Zisserman, A.: VoxCeleb2: deep speaker recognition. arXiv preprint arXiv:1806.05622 (2018)","DOI":"10.21437\/Interspeech.2018-1929"},{"key":"38_CR9","unstructured":"Deepfakes: Faceswap. https:\/\/github.com\/deepfakes\/faceswap"},{"key":"38_CR10","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\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4690\u20134699 (2019)","DOI":"10.1109\/CVPR.2019.00482"},{"issue":"5","key":"38_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3395208","volume":"39","author":"B Egger","year":"2020","unstructured":"Egger, B., et al.: 3D morphable face models-past, present, and future. ACM Trans. Graph. (TOG) 39(5), 1\u201338 (2020)","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"38_CR12","doi-asserted-by":"crossref","unstructured":"Gao, G., Huang, H., Fu, C., Li, Z., He, R.: Information bottleneck disentanglement for identity swapping. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3404\u20133413 (2021)","DOI":"10.1109\/CVPR46437.2021.00341"},{"key":"38_CR13","unstructured":"Goodfellow, I., et al.: Generative adversarial nets. In: Advances in Neural Information Processing Systems, vol. 27 (2014)"},{"key":"38_CR14","unstructured":"Guan, J., et al.: Delving into sequential patches for DeepFake detection. arXiv preprint arXiv:2207.02803 (2022)"},{"key":"38_CR15","doi-asserted-by":"crossref","unstructured":"Jiang, L., Li, R., Wu, W., Qian, C., Loy, C.C.: DeeperForensics-1.0: a large-scale dataset for real-world face forgery detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2889\u20132898 (2020)","DOI":"10.1109\/CVPR42600.2020.00296"},{"key":"38_CR16","unstructured":"Karras, T., Aila, T., Laine, S., Lehtinen, J.: Progressive growing of GANs for improved quality, stability, and variation. arXiv preprint arXiv:1710.10196 (2017)"},{"key":"38_CR17","unstructured":"Karras, T., et al.: Alias-free generative adversarial networks. In: Proceedings NeurIPS (2021)"},{"key":"38_CR18","doi-asserted-by":"crossref","unstructured":"Karras, T., Laine, S., Aila, T.: A style-based generator architecture for generative adversarial networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4401\u20134410 (2019)","DOI":"10.1109\/CVPR.2019.00453"},{"key":"38_CR19","doi-asserted-by":"crossref","unstructured":"Karras, T., Laine, S., Aittala, M., Hellsten, J., Lehtinen, J., Aila, T.: Analyzing and improving the image quality of StyleGAN. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 8110\u20138119 (2020)","DOI":"10.1109\/CVPR42600.2020.00813"},{"key":"38_CR20","doi-asserted-by":"crossref","unstructured":"Kim, H., et al.: Deep video portraits. ACM Trans. Graph. (TOG) 37, 1\u201314 (2018)","DOI":"10.1145\/3197517.3201283"},{"key":"38_CR21","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)"},{"key":"38_CR22","doi-asserted-by":"crossref","unstructured":"Korshunova, I., Shi, W., Dambre, J., Theis, L.: Fast face-swap using convolutional neural networks. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 3677\u20133685 (2017)","DOI":"10.1109\/ICCV.2017.397"},{"key":"38_CR23","unstructured":"Li, L., Bao, J., Yang, H., Chen, D., Wen, F.: FaceShifter: towards high fidelity and occlusion aware face swapping. In: CVPR (2020)"},{"key":"38_CR24","doi-asserted-by":"crossref","unstructured":"Liang, B., et al.: Expressive talking head generation with granular audio-visual control. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3387\u20133396, June 2022","DOI":"10.1109\/CVPR52688.2022.00338"},{"key":"38_CR25","doi-asserted-by":"crossref","unstructured":"Liu, Z., Luo, P., Wang, X., Tang, X.: Deep learning face attributes in the wild. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 3730\u20133738 (2015)","DOI":"10.1109\/ICCV.2015.425"},{"key":"38_CR26","doi-asserted-by":"crossref","unstructured":"Natsume, R., Yatagawa, T., Morishima, S.: RSGAN: face swapping and editing using face and hair representation in latent spaces. arXiv preprint arXiv:1804.03447 (2018)","DOI":"10.1145\/3230744.3230818"},{"key":"38_CR27","unstructured":"Nguyen, T.T., Nguyen, Q.V.H., Nguyen, C.M., Nguyen, D., Nguyen, D.T., Nahavandi, S.: Deep learning for DeepFakes creation and detection: a survey. arXiv preprint arXiv:1909.11573 (2019)"},{"key":"38_CR28","doi-asserted-by":"crossref","unstructured":"Nirkin, Y., Keller, Y., Hassner, T.: FSGAN: subject agnostic face swapping and reenactment. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 7184\u20137193 (2019)","DOI":"10.1109\/ICCV.2019.00728"},{"key":"38_CR29","doi-asserted-by":"crossref","unstructured":"Nirkin, Y., Masi, I., Tuan, A.T., Hassner, T., Medioni, G.: On face segmentation, face swapping, and face perception. In: 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018), pp. 98\u2013105. IEEE (2018)","DOI":"10.1109\/FG.2018.00024"},{"key":"38_CR30","doi-asserted-by":"crossref","unstructured":"Park, T., Liu, M.Y., Wang, T.C., Zhu, J.Y.: Semantic image synthesis with spatially-adaptive normalization. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2019)","DOI":"10.1109\/CVPR.2019.00244"},{"key":"38_CR31","doi-asserted-by":"crossref","unstructured":"Parkhi, O.M., Vedaldi, A., Zisserman, A.: Deep face recognition (2015)","DOI":"10.5244\/C.29.41"},{"key":"38_CR32","unstructured":"Perov, I., et al.: DeepFaceLab: integrated, flexible and extensible face-swapping framework. arXiv preprint arXiv:2005.05535 (2020)"},{"key":"38_CR33","doi-asserted-by":"crossref","unstructured":"Richardson, E., et al.: Encoding in style: a StyleGAN encoder for image-to-image translation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2287\u20132296 (2021)","DOI":"10.1109\/CVPR46437.2021.00232"},{"key":"38_CR34","doi-asserted-by":"crossref","unstructured":"R\u00f6ssler, A., Cozzolino, D., Verdoliva, L., Riess, C., Thies, J., Nie\u00dfner, M.: FaceForensics++: learning to detect manipulated facial images. In: International Conference on Computer Vision (ICCV) (2019)","DOI":"10.1109\/ICCV.2019.00009"},{"key":"38_CR35","doi-asserted-by":"crossref","unstructured":"Ruiz, N., Chong, E., Rehg, J.M.: Fine-grained head pose estimation without keypoints. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 2074\u20132083 (2018)","DOI":"10.1109\/CVPRW.2018.00281"},{"key":"38_CR36","unstructured":"Shen, Y., Yang, C., Tang, X., Zhou, B.: InterFaceGAN: interpreting the disentangled face representation learned by GANs. TPAMI (2020)"},{"key":"38_CR37","doi-asserted-by":"crossref","unstructured":"Shen, Y., Zhou, B.: Closed-form factorization of latent semantics in GANs. In: CVPR (2021)","DOI":"10.1109\/CVPR46437.2021.00158"},{"key":"38_CR38","doi-asserted-by":"crossref","unstructured":"Shu, C., et al.: Few-shot head swapping in the wild. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 10789\u201310798, June 2022","DOI":"10.1109\/CVPR52688.2022.01052"},{"key":"38_CR39","unstructured":"Sun, K., et al.: High-resolution representations for labeling pixels and regions. arXiv preprint arXiv:1904.04514 (2019)"},{"key":"38_CR40","doi-asserted-by":"crossref","unstructured":"Sun, Y., Zhou, H., Liu, Z., Koike, H.: Speech2Talking-Face: inferring and driving a face with synchronized audio-visual representation. In: IJCAI, vol. 2, p. 4 (2021)","DOI":"10.24963\/ijcai.2021\/141"},{"key":"38_CR41","doi-asserted-by":"crossref","unstructured":"Tov, O., Alaluf, Y., Nitzan, Y., Patashnik, O., Cohen-Or, D.: Designing an encoder for StyleGAN image manipulation. ACM Trans. Graph. (TOG) 40, 1\u201314 (2021)","DOI":"10.1145\/3476576.3476706"},{"key":"38_CR42","doi-asserted-by":"crossref","unstructured":"Vemulapalli, R., Agarwala, A.: A compact embedding for facial expression similarity. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5683\u20135692 (2019)","DOI":"10.1109\/CVPR.2019.00583"},{"key":"38_CR43","doi-asserted-by":"crossref","unstructured":"Wang, H., et al.: CosFace: large margin cosine loss for deep face recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5265\u20135274 (2018)","DOI":"10.1109\/CVPR.2018.00552"},{"key":"38_CR44","doi-asserted-by":"crossref","unstructured":"Wang, T.C., Liu, M.Y., Zhu, J.Y., Tao, A., Kautz, J., Catanzaro, B.: High-resolution image synthesis and semantic manipulation with conditional GANs. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2018)","DOI":"10.1109\/CVPR.2018.00917"},{"key":"38_CR45","doi-asserted-by":"crossref","unstructured":"Wang, T.C., Mallya, A., Liu, M.Y.: One-shot free-view neural talking-head synthesis for video conferencing. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10039\u201310049 (2021)","DOI":"10.1109\/CVPR46437.2021.00991"},{"key":"38_CR46","doi-asserted-by":"crossref","unstructured":"Wang, X., Li, Y., Zhang, H., Shan, Y.: Towards real-world blind face restoration with generative facial prior. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2021)","DOI":"10.1109\/CVPR46437.2021.00905"},{"key":"38_CR47","doi-asserted-by":"crossref","unstructured":"Wang, Y., et al.: HifiFace: 3D shape and semantic prior guided high fidelity face swapping. In: IJCAI (2021)","DOI":"10.24963\/ijcai.2021\/157"},{"key":"38_CR48","doi-asserted-by":"crossref","unstructured":"Xu, Y., Deng, B., Wang, J., Jing, Y., Pan, J., He, S.: High-resolution face swapping via latent semantics disentanglement. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 7642\u20137651, June 2022","DOI":"10.1109\/CVPR52688.2022.00749"},{"key":"38_CR49","doi-asserted-by":"crossref","unstructured":"Xu, Z., Hong, Z., Ding, C., Zhu, Z., Han, J., Liu, J., Ding, E.: MobileFaceSwap: a lightweight framework for video face swapping. In: AAAI (2022)","DOI":"10.1609\/aaai.v36i3.20203"},{"key":"38_CR50","doi-asserted-by":"crossref","unstructured":"Xu, Z., et al.: FaceController: controllable attribute editing for face in the wild. In: AAAI (2021)","DOI":"10.1609\/aaai.v35i4.16417"},{"key":"38_CR51","doi-asserted-by":"crossref","unstructured":"Yang, T., Ren, P., Xie, X., Zhang, L.: Gan prior embedded network for blind face restoration in the wild. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 672\u2013681 (2021)","DOI":"10.1109\/CVPR46437.2021.00073"},{"key":"38_CR52","doi-asserted-by":"crossref","unstructured":"Zhou, H., Sun, Y., Wu, W., Loy, C.C., Wang, X., Liu, Z.: Pose-controllable talking face generation by implicitly modularized audio-visual representation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2021)","DOI":"10.1109\/CVPR46437.2021.00416"},{"key":"38_CR53","doi-asserted-by":"crossref","unstructured":"Zhu, P., Abdal, R., Femiani, J., Wonka, P.: Barbershop: GAN-based image compositing using segmentation masks. arXiv preprint arXiv:2106.01505 (2021)","DOI":"10.1145\/3478513.3480537"},{"key":"38_CR54","doi-asserted-by":"crossref","unstructured":"Zhu, Y., Li, Q., Wang, J., Xu, C.Z., Sun, Z.: One shot face swapping on megapixels. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 4834\u20134844 (2021)","DOI":"10.1109\/CVPR46437.2021.00480"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2022"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-19781-9_38","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T16:44:18Z","timestamp":1710261858000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-19781-9_38"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031197802","9783031197819"],"references-count":54,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-19781-9_38","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"23 October 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Tel Aviv","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Israel","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 October 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 October 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2022.ecva.net\/","order":11,"name":"conference_url","label":"Conference URL","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":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"5804","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":"1645","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":"28% - 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":"3.21","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":"3.91","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)"}}]}}