{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T06:11:30Z","timestamp":1743142290665,"version":"3.40.3"},"publisher-location":"Cham","reference-count":32,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031581809"},{"type":"electronic","value":"9783031581816"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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\/978-3-031-58181-6_19","type":"book-chapter","created":{"date-parts":[[2024,7,2]],"date-time":"2024-07-02T10:03:42Z","timestamp":1719914622000},"page":"219-230","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["ExtSwap: Leveraging Extended Latent Mapper for\u00a0Generating High Quality Face Swapping"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1342-924X","authenticated-orcid":false,"given":"P. N.","family":"Aravinda Reddy","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6112-6887","authenticated-orcid":false,"given":"K.","family":"Sreenivasa Rao","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0484-3956","authenticated-orcid":false,"given":"Raghavendra","family":"Ramachandra","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1908-9813","authenticated-orcid":false,"given":"Pabitra","family":"Mitra","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,7,3]]},"reference":[{"key":"19_CR1","unstructured":"Korshunov, P., Marcel, S.: DeepFakes: a new threat to face recognition? Assessment and detection. arXiv preprint arXiv:1812.08685 (2018)"},{"key":"19_CR2","doi-asserted-by":"crossref","unstructured":"Li, Y., Chang, M.-C., Lyu, S.: In ictu oculi: exposing AI created fake videos by detecting eye blinking. In: IEEE International Workshop on Information Forensics and Security (WIFS) (2018)","DOI":"10.1109\/WIFS.2018.8630787"},{"key":"19_CR3","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":"19_CR4","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":"19_CR5","doi-asserted-by":"crossref","unstructured":"Shen, Y., Gu, J., Tang, X., Zhou, B.: Interpreting the latent space of GANs for semantic face editing. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9243\u20139252 (2020)","DOI":"10.1109\/CVPR42600.2020.00926"},{"key":"19_CR6","doi-asserted-by":"crossref","unstructured":"Tewari, A., Elgharib, M., Bharaj, G., Bernard, F., Seidel, H.P.: StyleRig: rigging StyleGAN for 3D control over portrait images. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6142\u20136151 (2020)","DOI":"10.1109\/CVPR42600.2020.00618"},{"key":"19_CR7","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":"19_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"592","DOI":"10.1007\/978-3-030-58520-4_35","volume-title":"Computer Vision \u2013 ECCV 2020","author":"J Zhu","year":"2020","unstructured":"Zhu, J., Shen, Y., Zhao, D., Zhou, B.: In-domain GAN inversion for real image editing. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12362, pp. 592\u2013608. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58520-4_35"},{"key":"19_CR9","unstructured":"Zhong, Y., Deng, W.: Face transformer for recognition. arXiv preprint arXiv:2103.14803 (2021)"},{"key":"19_CR10","unstructured":"Tan, M., Le, Q.: EfficientNetV2: smaller models and faster training. In: International Conference on Machine Learning, pp. 10096\u201310106 (2021)"},{"key":"19_CR11","unstructured":"Tan, M., Le, Q.: EfficientNet: rethinking model scaling for convolutional neural networks. In: International Conference on Machine Learning, pp. 6105\u20136114 (2019)"},{"key":"19_CR12","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 (2008)","DOI":"10.1145\/1399504.1360638"},{"key":"19_CR13","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":"19_CR14","doi-asserted-by":"crossref","unstructured":"Olszewski, K., Li, Z., Yang, C., Zhou, Y., Yu, R., Huang, Z.: Realistic dynamic facial textures from a single image using GANs. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 5429\u20135438 (2017)","DOI":"10.1109\/ICCV.2017.580"},{"key":"19_CR15","doi-asserted-by":"crossref","unstructured":"Sun, Q., Tewari, A., Xu, W., Fritz, M., Theobalt, C., Schiele, B.: A hybrid model for identity obfuscation by face replacement. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 553\u2013569 (2018)","DOI":"10.1007\/978-3-030-01246-5_34"},{"key":"19_CR16","doi-asserted-by":"crossref","unstructured":"Bao, J., Chen, D., Wen, F., Li, H., Hua, G.: Towards open-set identity preserving face synthesis. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 6713\u20136722 (2018)","DOI":"10.1109\/CVPR.2018.00702"},{"key":"19_CR17","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":"19_CR18","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":"19_CR19","unstructured":"Li, L., Bao, J., Yang, H., Chen, D., Wen, F.: FaceShifter: towards high fidelity and occlusion aware face swapping. arXiv preprint arXiv:1912.13457 (2019)"},{"key":"19_CR20","doi-asserted-by":"crossref","unstructured":"Naruniec, J., Helminger, L., Schroers, C., Weber, R.M.: High-resolution neural face swapping for visual effects. In: Computer Graphics Forum, pp. 173\u2013184 (2020)","DOI":"10.1111\/cgf.14062"},{"key":"19_CR21","unstructured":"Huang, H., He, R., Sun, Z., Tan, T.: IntroVAE: introspective variational autoencoders for photographic image synthesis. In: Advances in Neural Information Processing Systems, vol. 31 (2018)"},{"key":"19_CR22","doi-asserted-by":"crossref","unstructured":"Pidhorskyi, S., Adjeroh, D.A., Doretto, G.: Adversarial latent autoencoders. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 14104\u201314113 (2020)","DOI":"10.1109\/CVPR42600.2020.01411"},{"key":"19_CR23","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":"19_CR24","unstructured":"Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X.: An image is worth $$16\\times 16$$ words: transformers for image recognition at scale. arXiv preprint arXiv:2010.11929 (2020)"},{"key":"19_CR25","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"},{"key":"19_CR26","doi-asserted-by":"crossref","unstructured":"Chaudhuri, B., Vesdapunt, N., Wang, B.: Joint face detection and facial motion retargeting for multiple faces. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9719\u20139728 (2019)","DOI":"10.1109\/CVPR.2019.00995"},{"key":"19_CR27","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":"19_CR28","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":"19_CR29","doi-asserted-by":"crossref","unstructured":"Wang, Y., et al.: HifiFace: 3D shape and semantic prior guided high fidelity face swapping. arXiv preprint arXiv:2106.09965 (2021)","DOI":"10.24963\/ijcai.2021\/157"},{"key":"19_CR30","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, pp. 4834\u20134844 (2021)","DOI":"10.1109\/CVPR46437.2021.00480"},{"key":"19_CR31","doi-asserted-by":"crossref","unstructured":"Nitzan, Y., Bermano, A., Li, Y., Cohen-Or, D.: Face identity disentanglement via latent space mapping. arXiv preprint arXiv:2005.07728 (2020)","DOI":"10.1145\/3414685.3417826"},{"key":"19_CR32","doi-asserted-by":"crossref","unstructured":"Liu, Z., Luo, P., Wang, X., Tang, X.: Deep learning face attributes in the wild. In: Proceedings of International Conference on Computer Vision (ICCV) (2015)","DOI":"10.1109\/ICCV.2015.425"}],"container-title":["Communications in Computer and Information Science","Computer Vision and Image Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-58181-6_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,2]],"date-time":"2024-07-02T10:07:46Z","timestamp":1719914866000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-58181-6_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031581809","9783031581816"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-58181-6_19","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"3 July 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CVIP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computer Vision and Image Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Jammu","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","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":"3 November 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 November 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cvip2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/iitjammu.ac.in\/cvip2023\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Online CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"461","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":"140","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":"30% - 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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}