{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T18:33:45Z","timestamp":1770834825526,"version":"3.50.1"},"publisher-location":"Cham","reference-count":44,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031733826","type":"print"},{"value":"9783031733833","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,11,3]],"date-time":"2024-11-03T00:00:00Z","timestamp":1730592000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,3]],"date-time":"2024-11-03T00:00:00Z","timestamp":1730592000000},"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\/978-3-031-73383-3_20","type":"book-chapter","created":{"date-parts":[[2024,11,2]],"date-time":"2024-11-02T12:05:05Z","timestamp":1730549105000},"page":"340-356","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Toward Tiny and\u00a0High-Quality Facial Makeup with\u00a0Data Amplify Learning"],"prefix":"10.1007","author":[{"given":"Qiaoqiao","family":"Jin","sequence":"first","affiliation":[]},{"given":"Xuanhong","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Meiguang","family":"Jin","sequence":"additional","affiliation":[]},{"given":"Ying","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Rui","family":"Shi","sequence":"additional","affiliation":[]},{"given":"Yucheng","family":"Zheng","sequence":"additional","affiliation":[]},{"given":"Yupeng","family":"Zhu","sequence":"additional","affiliation":[]},{"given":"Bingbing","family":"Ni","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,11,3]]},"reference":[{"key":"20_CR1","doi-asserted-by":"crossref","unstructured":"Chen, R., Chen, X., Ni, B., Ge, Y.: Simswap: an efficient framework for high fidelity face swapping. In: MM 2020: The 28th ACM International Conference on Multimedia, Virtual Event\/Seattle, WA, USA, 12\u201316 October 2020, pp. 2003\u20132011. ACM (2020)","DOI":"10.1145\/3394171.3413630"},{"key":"20_CR2","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"670","DOI":"10.1007\/978-3-030-58621-8_39","volume-title":"Computer Vision \u2013 ECCV 2020","author":"X Chen","year":"2020","unstructured":"Chen, X., et al.: CooGAN: a memory-efficient framework for high-resolution facial attribute editing. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12356, pp. 670\u2013686. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58621-8_39"},{"issue":"1","key":"20_CR3","doi-asserted-by":"publisher","first-page":"576","DOI":"10.1109\/TPAMI.2023.3307156","volume":"46","author":"X Chen","year":"2024","unstructured":"Chen, X., Ni, B., Liu, Y., Liu, N., Zeng, Z., Wang, H.: Simswap++: towards faster and high-quality identity swapping. IEEE Trans. Pattern Anal. Mach. Intell. 46(1), 576\u2013592 (2024)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"20_CR4","doi-asserted-by":"crossref","unstructured":"Chen, X., Yan, X., Liu, N., Qiu, T., Ni, B.: Anisotropic stroke control for multiple artists style transfer. In: MM 2020: The 28th ACM International Conference on Multimedia, Virtual Event\/Seattle, WA, USA, 12\u201316 October 2020, pp. 3246\u20133255. ACM (2020)","DOI":"10.1145\/3394171.3413770"},{"key":"20_CR5","unstructured":"https:\/\/github.com\/apple\/coremltools"},{"key":"20_CR6","doi-asserted-by":"crossref","unstructured":"Deng, H., Han, C., Cai, H., Han, G., He, S.: Spatially-invariant style-codes controlled makeup transfer. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2021, virtual, 19\u201325 June 2021, pp. 6549\u20136557. Computer Vision Foundation\/IEEE (2021)","DOI":"10.1109\/CVPR46437.2021.00648"},{"key":"20_CR7","doi-asserted-by":"crossref","unstructured":"Deng, J., Guo, J., Zafeiriou, S.: Arcface: additive angular margin loss for deep face recognition. CoRR abs\/1801.07698 (2018)","DOI":"10.1109\/CVPR.2019.00482"},{"key":"20_CR8","unstructured":"Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: Bert: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)"},{"key":"20_CR9","first-page":"8780","volume":"34","author":"P Dhariwal","year":"2021","unstructured":"Dhariwal, P., Nichol, A.: Diffusion models beat GANs on image synthesis. Adv. Neural. Inf. Process. Syst. 34, 8780\u20138794 (2021)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"20_CR10","unstructured":"(2021). https:\/\/github.com\/mlfoundations\/open_clip"},{"key":"20_CR11","unstructured":"Gal, R., et al.: An image is worth one word: Personalizing text-to-image generation using textual inversion. arXiv preprint arXiv:2208.01618 (2022)"},{"key":"20_CR12","unstructured":"Goodfellow, I., et al.: Generative adversarial nets. In: Advances in Neural Information Processing Systems, vol. 27 (2014)"},{"key":"20_CR13","doi-asserted-by":"crossref","unstructured":"Guo, D., Sim, T.: Digital face makeup by example. In: 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), 20\u201325 June 2009, Miami, Florida, USA, pp. 73\u201379. IEEE Computer Society (2009)","DOI":"10.1109\/CVPR.2009.5206833"},{"key":"20_CR14","unstructured":"Ho, J., Jain, A., Abbeel, P.: Denoising diffusion probabilistic models (2020)"},{"key":"20_CR15","unstructured":"Hu, E.J., et al.: Lora: low-rank adaptation of large language models. In: The Tenth International Conference on Learning Representations, ICLR 2022, Virtual Event, 25\u201329 April 2022. OpenReview.net (2022)"},{"key":"20_CR16","doi-asserted-by":"crossref","unstructured":"Isola, P., Zhu, J., Zhou, T., Efros, A.A.: Image-to-image translation with conditional adversarial networks. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, Honolulu, HI, USA, 21\u201326 July 2017, pp. 5967\u20135976. IEEE Computer Society (2017)","DOI":"10.1109\/CVPR.2017.632"},{"key":"20_CR17","doi-asserted-by":"crossref","unstructured":"Jiang, W., Liu, S., Gao, C., Cao, J., He, R., Feng, J., Yan, S.: PSGAN: pose and expression robust spatial-aware GAN for customizable makeup transfer. In: 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2020, Seattle, WA, USA, 13\u201319 June 2020, pp. 5193\u20135201. Computer Vision Foundation\/IEEE (2020)","DOI":"10.1109\/CVPR42600.2020.00524"},{"key":"20_CR18","doi-asserted-by":"crossref","unstructured":"Karras, T., Laine, S., Aila, T.: A style-based generator architecture for generative adversarial networks. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2019, Long Beach, CA, USA, 16\u201320 June 2019, pp. 4401\u20134410. Computer Vision Foundation\/IEEE (2019)","DOI":"10.1109\/CVPR.2019.00453"},{"key":"20_CR19","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. In: Bengio, Y., LeCun, Y. (eds.) 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, 7\u20139 May 2015, Conference Track Proceedings (2015)"},{"key":"20_CR20","doi-asserted-by":"crossref","unstructured":"Li, C., Zhou, K., Lin, S.: Simulating makeup through physics-based manipulation of intrinsic image layers. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015, Boston, MA, USA, 7\u201312 June 2015, pp. 4621\u20134629. IEEE Computer Society (2015)","DOI":"10.1109\/CVPR.2015.7299093"},{"key":"20_CR21","doi-asserted-by":"crossref","unstructured":"Li, T., et al.: Beautygan: instance-level facial makeup transfer with deep generative adversarial network. In: 2018 ACM Multimedia Conference on Multimedia Conference, MM 2018, Seoul, Republic of Korea, 22\u201326 October 2018, pp. 645\u2013653. ACM (2018)","DOI":"10.1145\/3240508.3240618"},{"key":"20_CR22","unstructured":"Liu, X., et al.: Face beautification: beyond makeup transfer. CoRR abs\/1912.03630 (2019). http:\/\/arxiv.org\/abs\/1912.03630"},{"key":"20_CR23","doi-asserted-by":"crossref","unstructured":"Lyu, Y., Dong, J., Peng, B., Wang, W., Tan, T.: SOGAN: 3D-aware shadow and occlusion robust GAN for makeup transfer. CoRR abs\/2104.10567 (2021)","DOI":"10.1145\/3474085.3475531"},{"key":"20_CR24","unstructured":"Nichol, A., et al.: Glide: towards photorealistic image generation and editing with text-guided diffusion models. arXiv preprint arXiv:2112.10741 (2021)"},{"key":"20_CR25","unstructured":"(2022). https:\/\/github.com\/huggingface\/"},{"key":"20_CR26","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1007\/978-3-030-67832-6_4","volume-title":"MultiMedia Modeling","author":"T Qiu","year":"2021","unstructured":"Qiu, T., Ni, B., Liu, Z., Chen, X.: Fast optimal transport artistic style transfer. In: Loko\u010d, J., et al. (eds.) MMM 2021. LNCS, vol. 12572, pp. 37\u201349. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-67832-6_4"},{"key":"20_CR27","unstructured":"Radford, A., et al.: Learning transferable visual models from natural language supervision. In: International Conference on Machine Learning, pp. 8748\u20138763. PMLR (2021)"},{"key":"20_CR28","doi-asserted-by":"crossref","unstructured":"Rombach, R., Blattmann, A., Lorenz, D., Esser, P., Ommer, B.: High-resolution image synthesis with latent diffusion models. In: IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022, New Orleans, LA, USA, 18\u201324 June 2022, pp. 10674\u201310685. IEEE (2022)","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"20_CR29","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1007\/978-3-319-24574-4_28","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015","author":"O Ronneberger","year":"2015","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-Net: convolutional networks for biomedical image segmentation. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9351, pp. 234\u2013241. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28"},{"key":"20_CR30","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: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 22500\u201322510 (2023)","DOI":"10.1109\/CVPR52729.2023.02155"},{"key":"20_CR31","doi-asserted-by":"crossref","unstructured":"Saharia, C., et al.: Palette: image-to-image diffusion models. In: ACM SIGGRAPH 2022 Conference Proceedings, pp. 1\u201310 (2022)","DOI":"10.1145\/3528233.3530757"},{"key":"20_CR32","first-page":"36479","volume":"35","author":"C Saharia","year":"2022","unstructured":"Saharia, C., et al.: Photorealistic text-to-image diffusion models with deep language understanding. Adv. Neural. Inf. Process. Syst. 35, 36479\u201336494 (2022)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"20_CR33","unstructured":"https:\/\/huggingface.co\/lambdalabs\/sd-image-variations-diffusers"},{"key":"20_CR34","unstructured":"Song, J., Meng, C., Ermon, S.: Denoising diffusion implicit models. arXiv preprint arXiv:2010.02502 (2020)"},{"key":"20_CR35","unstructured":"https:\/\/huggingface.co\/runwayml\/stable-diffusion-v1-5"},{"key":"20_CR36","unstructured":"https:\/\/huggingface.co\/stabilityai\/stable-diffusion-2-1-unclip"},{"key":"20_CR37","unstructured":"Wan, Z., Chen, H., Zhang, J., Jiang, W., Yao, C., Luo, J.: Facial attribute transformers for precise and robust makeup transfer. CoRR abs\/2104.02894 (2021)"},{"key":"20_CR38","unstructured":"Wang, Q., et al.: Instantid: zero-shot identity-preserving generation in seconds (2024)"},{"key":"20_CR39","doi-asserted-by":"crossref","unstructured":"Yan, Q., Guo, C., Zhao, J., Dai, Y., Loy, C.C., Li, C.: Beautyrec: robust, efficient, and component-specific makeup transfer. In: IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023 - Workshops, Vancouver, BC, Canada, 17\u201324 June 2023, pp. 1102\u20131110. IEEE (2023)","DOI":"10.1109\/CVPRW59228.2023.00117"},{"key":"20_CR40","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"737","DOI":"10.1007\/978-3-031-19787-1_42","volume-title":"Computer Vision - ECCV 2022, Part XVI","author":"C Yang","year":"2022","unstructured":"Yang, C., He, W., Xu, Y., Gao, Y.: Elegant: exquisite and locally editable GAN for makeup transfer. In: Avidan, S., Brostow, G.J., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022, Part XVI. LNCS, vol. 13676, pp. 737\u2013754. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-19787-1_42"},{"key":"20_CR41","unstructured":"Ye, H., Zhang, J., Liu, S., Han, X., Yang, W.: IP-adapter: text compatible image prompt adapter for text-to-image diffusion models. CoRR abs\/2308.06721 (2023)"},{"key":"20_CR42","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"334","DOI":"10.1007\/978-3-030-01261-8_20","volume-title":"Computer Vision \u2013 ECCV 2018","author":"C Yu","year":"2018","unstructured":"Yu, C., Wang, J., Peng, C., Gao, C., Yu, G., Sang, N.: BiSeNet: bilateral segmentation network for real-time semantic segmentation. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11217, pp. 334\u2013349. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01261-8_20"},{"key":"20_CR43","doi-asserted-by":"crossref","unstructured":"Zhang, L., Rao, A., Agrawala, M.: Adding conditional control to text-to-image diffusion models. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 3836\u20133847 (2023)","DOI":"10.1109\/ICCV51070.2023.00355"},{"key":"20_CR44","unstructured":"Zheng, Y., et al.: General facial representation learning in a visual-linguistic manner. CoRR abs\/2112.03109 (2021)"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2024"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-73383-3_20","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,2]],"date-time":"2024-11-02T12:10:51Z","timestamp":1730549451000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-73383-3_20"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,3]]},"ISBN":["9783031733826","9783031733833"],"references-count":44,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-73383-3_20","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,3]]},"assertion":[{"value":"3 November 2024","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":"Milan","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 September 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2024.ecva.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}