{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T15:32:34Z","timestamp":1784302354428,"version":"3.55.0"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032006370","type":"print"},{"value":"9783032006356","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[[2025]]},"DOI":"10.1007\/978-3-032-00635-6_9","type":"book-chapter","created":{"date-parts":[[2025,8,8]],"date-time":"2025-08-08T13:36:20Z","timestamp":1754660180000},"page":"153-170","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Generating Deepfakes with\u00a0Stable Diffusion, ControlNet, and\u00a0LoRA"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7411-9678","authenticated-orcid":false,"given":"Stefano","family":"Bistarelli","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3935-4696","authenticated-orcid":false,"given":"Francesco","family":"Santini","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Edoardo Toma","family":"Tavassi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,8,9]]},"reference":[{"key":"9_CR1","unstructured":"Bazarevsky, V., Kartynnik, Y., Vakunov, A., Raveendran, K., Grundmann, M.: Blazeface: sub-millisecond neural face detection on mobile GPUs. CoRR abs\/1907.05047 (2019)"},{"key":"9_CR2","unstructured":"Bonettini, N., Cannas, E.D., Mandelli, S., Bondi, L., Bestagini, P., Tubaro, S.: Video face manipulation detection through ensemble of CNNs (2020). https:\/\/arxiv.org\/abs\/2004.07676"},{"key":"9_CR3","unstructured":"Gal, R., et al.: An image is worth one word: Personalizing text-to-image generation using textual inversion. In: ICLR. OpenReview.net, Kigali, Rwanda (2023)"},{"issue":"4","key":"9_CR4","doi-asserted-by":"publisher","first-page":"132","DOI":"10.1016\/0020-0190(72)90045-2","volume":"1","author":"RL Graham","year":"1972","unstructured":"Graham, R.L.: An efficient algorithm for determining the convex hull of a finite planar set. Inf. Process. Lett. 1(4), 132\u2013133 (1972)","journal-title":"Inf. Process. Lett."},{"key":"9_CR5","doi-asserted-by":"crossref","unstructured":"G\u00fcera, D., Delp, E.J.: Deepfake video detection using recurrent neural networks. In: International Conference on Advanced Video and Signal Based Surveillance, pp.\u00a01\u20136. IEEE (2018)","DOI":"10.1109\/AVSS.2018.8639163"},{"key":"9_CR6","doi-asserted-by":"crossref","unstructured":"Guillaro, F., Cozzolino, D., Sud, A., Dufour, N., Verdoliva, L.: Trufor: leveraging all-round clues for trustworthy image forgery detection and localization (2023). https:\/\/arxiv.org\/abs\/2212.10957","DOI":"10.1109\/CVPR52729.2023.01974"},{"key":"9_CR7","unstructured":"Ho, J., Salimans, T.: Classifier-free diffusion guidance. CoRR abs\/2207.12598 (2022)"},{"key":"9_CR8","unstructured":"Hu, E.J., et al.: LoRA: low-rank adaptation of large language models. In: ICLR, OpenReview.net, Virtual event (2022)"},{"key":"9_CR9","unstructured":"Kartynnik, Y., Ablavatski, A., Grishchenko, I., Grundmann, M.: Real-time facial surface geometry from monocular video on mobile GPUs. CoRR abs\/1907.06724 (2019)"},{"key":"9_CR10","doi-asserted-by":"crossref","unstructured":"Korshunova, I., Shi, W., Dambre, J., Theis, L.: Fast face-swap using convolutional neural networks. In: IEEE International Conference on Computer Vision, ICCV, pp. 3697\u20133705. IEEE Computer Society (2017)","DOI":"10.1109\/ICCV.2017.397"},{"key":"9_CR11","doi-asserted-by":"crossref","unstructured":"Kushwaha, V., Nandi, G.: Study of prevention of mode collapse in generative adversarial network (GAN). In: 2020 IEEE 4th Conference on Information and Communication Technology (CICT), pp.\u00a01\u20136. IEEE (2020)","DOI":"10.1109\/CICT51604.2020.9312049"},{"key":"9_CR12","unstructured":"Li, J., Li, D., Xiong, C., Hoi, S.C.H.: BLIP: bootstrapping language-image pre-training for unified vision-language understanding and generation. In: ICML. Proceedings of Machine Learning Research, vol.\u00a0162, pp. 12888\u201312900. PMLR (2022)"},{"key":"9_CR13","doi-asserted-by":"crossref","unstructured":"Natsume, R., Yatagawa, T., Morishima, S.: FSnet: an identity-aware generative model for image-based face swapping. In: ACCV (6). LNCS, vol. 11366, pp. 117\u2013132. Springer, Cham (2018)","DOI":"10.1007\/978-3-030-20876-9_8"},{"key":"9_CR14","doi-asserted-by":"crossref","unstructured":"Natsume, R., Yatagawa, T., Morishima, S.: RSGAN: face swapping and editing using face and hair representation in latent spaces. In: SIGGRAPH Posters, pp. 69:1\u201369:2. ACM (2018)","DOI":"10.1145\/3230744.3230818"},{"key":"9_CR15","doi-asserted-by":"crossref","unstructured":"Nguyen, T.T., et al.: Deep learning for deepfakes creation and detection: a survey. Comp. Vision Image Underst. 223 (2022)","DOI":"10.1016\/j.cviu.2022.103525"},{"key":"9_CR16","doi-asserted-by":"crossref","unstructured":"Nirkin, Y., Keller, Y., Hassner, T.: FSGAN: subject agnostic face swapping and reenactment. In: ICCV, pp. 7183\u20137192. IEEE (2019)","DOI":"10.1109\/ICCV.2019.00728"},{"key":"9_CR17","doi-asserted-by":"crossref","unstructured":"Pech-Pacheco, J.L., Cristobal, G., Chamorro-Martinez, J., Fernandez-Valdivia, J.: Diatom autofocusing in brightfield microscopy: a comparative study. In: Proceedings of ICPR, vol.\u00a03, pp. 314\u2013317 (2000)","DOI":"10.1109\/ICPR.2000.903548"},{"key":"9_CR18","doi-asserted-by":"publisher","first-page":"25494","DOI":"10.1109\/ACCESS.2022.3154404","volume":"10","author":"MS Rana","year":"2022","unstructured":"Rana, M.S., Nobi, M.N., Murali, B., Sung, A.H.: Deepfake detection: a systematic literature review. IEEE Access 10, 25494\u201325513 (2022)","journal-title":"IEEE Access"},{"key":"9_CR19","doi-asserted-by":"crossref","unstructured":"Rombach, R., Blattmann, A., Lorenz, D., Esser, P., Ommer, B.: High-resolution image synthesis with latent diffusion models. In: CVPR, pp. 10674\u201310685. IEEE (2022)","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"9_CR20","doi-asserted-by":"crossref","unstructured":"Ruiz, N., Li, Y., Jampani, V., Pritch, Y., Rubinstein, M., Aberman, K.: Dreambooth: fine tuning text-to-image diffusion models for subject-driven generation. In: CVPR, pp. 22500\u201322510. IEEE (2023)","DOI":"10.1109\/CVPR52729.2023.02155"},{"key":"9_CR21","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1007\/978-3-642-33712-3_4","volume-title":"Computer Vision \u2013 ECCV 2012","author":"BM Smith","year":"2012","unstructured":"Smith, B.M., Zhang, L.: Joint face alignment with non-parametric shape models. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012. LNCS, vol. 7574, pp. 43\u201356. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-33712-3_4"},{"key":"9_CR22","doi-asserted-by":"crossref","unstructured":"Teh, S., Perumal, V., Hamid, H.: Investigating how frame rates in different styles of animation affect the psychology of the audience. Int. J. Creative Multimedia 4, 10\u201331 (2023)","DOI":"10.33093\/ijcm.2023.4.2.2"},{"issue":"6","key":"9_CR23","doi-asserted-by":"publisher","first-page":"607","DOI":"10.1049\/bme2.12031","volume":"10","author":"P Yu","year":"2021","unstructured":"Yu, P., Xia, Z., Fei, J., Lu, Y.: A survey on deepfake video detection. IET Biom. 10(6), 607\u2013624 (2021)","journal-title":"IET Biom."},{"key":"9_CR24","doi-asserted-by":"crossref","unstructured":"Zhang, L., Agrawala, M.: Adding conditional control to text-to-image diffusion models. CoRR abs\/2302.05543 (2023)","DOI":"10.1109\/ICCV51070.2023.00355"},{"issue":"5","key":"9_CR25","doi-asserted-by":"publisher","first-page":"6259","DOI":"10.1007\/s11042-021-11733-y","volume":"81","author":"T Zhang","year":"2022","unstructured":"Zhang, T.: Deepfake generation and detection, a survey. Multimedia Tools Appl. 81(5), 6259\u20136276 (2022)","journal-title":"Multimedia Tools Appl."}],"container-title":["Lecture Notes in Computer Science","Availability, Reliability and Security"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-00635-6_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,8]],"date-time":"2025-09-08T19:28:24Z","timestamp":1757359704000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-00635-6_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783032006370","9783032006356"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-00635-6_9","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"9 August 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ARES","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Availability, Reliability and Security","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ghent","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Belgium","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 August 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 August 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ares-12025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/2025.ares-conference.eu","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}