{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T11:42:18Z","timestamp":1761824538715,"version":"3.41.0"},"publisher-location":"Cham","reference-count":79,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031920882","type":"print"},{"value":"9783031920899","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\/978-3-031-92089-9_15","type":"book-chapter","created":{"date-parts":[[2025,5,24]],"date-time":"2025-05-24T12:48:49Z","timestamp":1748090929000},"page":"227-246","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Makeup-Guided Facial Privacy Protection via\u00a0Untrained Neural Network Priors"],"prefix":"10.1007","author":[{"given":"Fahad","family":"Shamshad","sequence":"first","affiliation":[]},{"given":"Muzammal","family":"Naseer","sequence":"additional","affiliation":[]},{"given":"Karthik","family":"Nandakumar","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,5,12]]},"reference":[{"key":"15_CR1","doi-asserted-by":"crossref","unstructured":"Ahern, S., Eckles, D., Good, N.S., King, S., Naaman, M., Nair, R.: Over-exposed? Privacy patterns and considerations in online and mobile photo sharing. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 357\u2013366 (2007)","DOI":"10.1145\/1240624.1240683"},{"key":"15_CR2","doi-asserted-by":"crossref","unstructured":"Asim, M., Shamshad, F., Ahmed, A.: Blind image deconvolution using pretrained generative priors. arXiv preprint arXiv:1908.07404 (2019)","DOI":"10.1109\/TCI.2020.3032671"},{"key":"15_CR3","unstructured":"Asim, M., Shamshad, F., Ahmed, A.: PatchDIP exploiting patch redundancy in deep image prior for denoising. In: NeurIPS 2019 Workshop on Solving Inverse Problems with Deep Networks (2019)"},{"key":"15_CR4","doi-asserted-by":"publisher","first-page":"1493","DOI":"10.1109\/TCI.2020.3032671","volume":"6","author":"M Asim","year":"2020","unstructured":"Asim, M., Shamshad, F., Ahmed, A.: Blind image deconvolution using deep generative priors. IEEE Trans. Comput. Imaging 6, 1493\u20131506 (2020)","journal-title":"IEEE Trans. Comput. Imaging"},{"key":"15_CR5","doi-asserted-by":"crossref","unstructured":"Bar-Tal, O., Ofri-Amar, D., Fridman, R., Kasten, Y., Dekel, T.: Text2Live: text-driven layered image and video editing. In: European Conference on Computer Vision, pp. 707\u2013723. Springer (2022)","DOI":"10.1007\/978-3-031-19784-0_41"},{"key":"15_CR6","unstructured":"Bhattad, A., Chong, M.J., Liang, K., Li, B., Forsyth, D.A.: Unrestricted adversarial examples via semantic manipulation. arXiv preprint arXiv:1904.06347 (2019)"},{"key":"15_CR7","doi-asserted-by":"crossref","unstructured":"Caron, M., et al.: Emerging properties in self-supervised vision transformers. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 9650\u20139660 (2021)","DOI":"10.1109\/ICCV48922.2021.00951"},{"key":"15_CR8","doi-asserted-by":"crossref","unstructured":"Chen, S., Liu, Y., Gao, X., Han, Z.: MobileFaceNets: efficient CNNs for accurate real-time face verification on mobile devices. In: Chinese Conference on Biometric Recognition, pp. 428\u2013438. Springer (2018)","DOI":"10.1007\/978-3-319-97909-0_46"},{"key":"15_CR9","unstructured":"Cherepanova, V., et al.: LowKey: leveraging adversarial attacks to protect social media users from facial recognition. In: International Conference on Learning Representations (2020)"},{"key":"15_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"},{"key":"15_CR11","doi-asserted-by":"crossref","unstructured":"Dong, Y., et al.: Boosting adversarial attacks with momentum. In: Proceedings of the 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR\u201918), pp. 9185\u20139193 (2018)","DOI":"10.1109\/CVPR.2018.00957"},{"key":"15_CR12","doi-asserted-by":"crossref","unstructured":"Dong, Y., Pang, T., Su, H., Zhu, J.: Evading defenses to transferable adversarial examples by translation-invariant attacks. In: Proceedings of the 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR\u201919), pp. 4312\u20134321 (2019)","DOI":"10.1109\/CVPR.2019.00444"},{"key":"15_CR13","doi-asserted-by":"crossref","unstructured":"Gu, Q., Wang, G., Chiu, M.T., Tai, Y.W., Tang, C.K.: LADN: local adversarial disentangling network for facial makeup and de-makeup. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 10481\u201310490 (2019)","DOI":"10.1109\/ICCV.2019.01058"},{"key":"15_CR14","doi-asserted-by":"crossref","unstructured":"Gu, S., Bao, J., Yang, H., Chen, D., Wen, F., Yuan, L.: Mask-guided portrait editing with conditional GANs. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3436\u20133445 (2019)","DOI":"10.1109\/CVPR.2019.00355"},{"key":"15_CR15","unstructured":"Guetta, N., Shabtai, A., Singh, I., Momiyama, S., Elovici, Y.: Dodging attack using carefully crafted natural makeup. arXiv preprint arXiv:2109.06467 (2021)"},{"issue":"4","key":"15_CR16","first-page":"1","volume":"37","author":"M He","year":"2018","unstructured":"He, M., Chen, D., Liao, J., Sander, P.V., Yuan, L.: Deep exemplar-based colorization. ACM Trans. Graph. (TOG) 37(4), 1\u201316 (2018)","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"15_CR17","unstructured":"Heusel, M., Ramsauer, H., Unterthiner, T., Nessler, B., Hochreiter, S.: GANs trained by a two time-scale update rule converge to a local Nash equilibrium. Adv. Neural Inf. Process. Syst. 30 (2017)"},{"key":"15_CR18","doi-asserted-by":"crossref","unstructured":"Hong, S., Kim, S.: Deep matching prior: test-time optimization for dense correspondence. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 9907\u20139917 (2021)","DOI":"10.1109\/ICCV48922.2021.00976"},{"key":"15_CR19","doi-asserted-by":"crossref","unstructured":"Hu, J., Shen, L., Sun, G.: Squeeze-and-excitation networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7132\u20137141 (2018)","DOI":"10.1109\/CVPR.2018.00745"},{"key":"15_CR20","doi-asserted-by":"crossref","unstructured":"Hu, S., Liu, X., Zhang, Y., Li, M., Zhang, L.Y., Jin, H., Wu, L.: Protecting facial privacy: generating adversarial identity masks via style-robust makeup transfer. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 15014\u201315023 (2022)","DOI":"10.1109\/CVPR52688.2022.01459"},{"key":"15_CR21","unstructured":"Huang, G.B., Mattar, M., Berg, T., Learned-Miller, E.: Labeled faces in the wild: a database for studying face recognition in unconstrained environments. In: Workshop on faces in \u2019Real-Life\u2019 Images: Detection, Alignment, and Recognition (2008)"},{"key":"15_CR22","doi-asserted-by":"crossref","unstructured":"Jung, C., Kwon, G., Ye, J.C.: Exploring patch-wise semantic relation for contrastive learning in image-to-image translation tasks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 18260\u201318269 (2022)","DOI":"10.1109\/CVPR52688.2022.01772"},{"key":"15_CR23","unstructured":"Kakizaki, K., Yoshida, K.: Adversarial image translation: Unrestricted adversarial examples in face recognition systems. arXiv preprint arXiv:1905.03421 (2019)"},{"issue":"10","key":"15_CR24","doi-asserted-by":"publisher","first-page":"1925","DOI":"10.1109\/TPAMI.2011.68","volume":"33","author":"B Kamgar-Parsi","year":"2011","unstructured":"Kamgar-Parsi, B., Lawson, W., Kamgar-Parsi, B.: Toward development of a face recognition system for watchlist surveillance. IEEE Trans. Pattern Anal. Mach. Intell. 33(10), 1925\u20131937 (2011)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"15_CR25","doi-asserted-by":"crossref","unstructured":"Karakas, C.E., Dirik, A., Yal\u00e7\u0131nkaya, E., Yanardag, P.: FairStyle: debiasing StyleGAN2 with style channel manipulations. In: European Conference on Computer Vision, pp. 570\u2013586. Springer (2022)","DOI":"10.1007\/978-3-031-19778-9_33"},{"key":"15_CR26","unstructured":"Karras, T., Aila, T., Laine, S., Lehtinen, J.: Progressive growing of GANs for improved quality, stability, and variation. In: International Conference on Learning Representations (2018)"},{"key":"15_CR27","unstructured":"Kingma, D.P., Ba, J.: Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)"},{"key":"15_CR28","doi-asserted-by":"crossref","unstructured":"Komkov, S., Petiushko, A.: AdvHat: real-world adversarial attack on ArcFace face ID system. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 819\u2013826. IEEE (2021)","DOI":"10.1109\/ICPR48806.2021.9412236"},{"key":"15_CR29","doi-asserted-by":"crossref","unstructured":"Li, T., et al.: BeautyGAN: instance-level facial makeup transfer with deep generative adversarial network. In: Proceedings of the 26th ACM International Conference on Multimedia, pp. 645\u2013653 (2018)","DOI":"10.1145\/3240508.3240618"},{"key":"15_CR30","first-page":"7838","volume":"34","author":"X Li","year":"2021","unstructured":"Li, X., Kaesemodel Pontes, J., Lucey, S.: Neural scene flow prior. Adv. Neural. Inf. Process. Syst. 34, 7838\u20137851 (2021)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"15_CR31","doi-asserted-by":"crossref","unstructured":"Liu, F., Zhang, C., Zhang, H.: Towards transferable unrestricted adversarial examples with minimum changes. arXiv preprint arXiv:2201.01102 (2022)","DOI":"10.1109\/SaTML54575.2023.00030"},{"issue":"5","key":"15_CR32","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0196391","volume":"13","author":"SR Livingstone","year":"2018","unstructured":"Livingstone, S.R., Russo, F.A.: The Ryerson audio-visual database of emotional speech and song (RAVDESS): a dynamic, multimodal set of facial and vocal expressions in north American English. PLoS ONE 13(5), e0196391 (2018)","journal-title":"PLoS ONE"},{"key":"15_CR33","unstructured":"Madry, A., Makelov, A., Schmidt, L., Tsipras, D., Vladu, A.: Towards deep learning models resistant to adversarial attacks. In: Proceedings of the 6th International Conference on Learning Representations (ICLR\u201918) (2018)"},{"key":"15_CR34","doi-asserted-by":"crossref","unstructured":"Masi, I., Mathai, J., AbdAlmageed, W.: Towards learning structure via consensus for face segmentation and parsing. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5508\u20135518 (2020)","DOI":"10.1109\/CVPR42600.2020.00555"},{"key":"15_CR35","unstructured":"Mataev, G., Milanfar, P., Elad, M.: DeepRED: deep image prior powered by red. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision Workshops (2019)"},{"key":"15_CR36","doi-asserted-by":"crossref","unstructured":"Meden, B., et al.: Privacy\u2013enhancing face biometrics: a comprehensive survey. IEEE Transactions on Information Forensics and Security (2021)","DOI":"10.1109\/TIFS.2021.3096024"},{"key":"15_CR37","unstructured":"Mu\u00f1oz, C., Zannone, S., Mohammed, U., Koshiyama, A.: Uncovering bias in face generation models. arXiv preprint arXiv:2302.11562 (2023)"},{"key":"15_CR38","doi-asserted-by":"crossref","unstructured":"Nguyen, T., Tran, A.T., Hoai, M.: Lipstick ain\u2019t enough: beyond color matching for in-the-wild makeup transfer. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 13305\u201313314 (2021)","DOI":"10.1109\/CVPR46437.2021.01310"},{"key":"15_CR39","doi-asserted-by":"crossref","unstructured":"Oh, S.J., Fritz, M., Schiele, B.: Adversarial image perturbation for privacy protection a game theory perspective. In: 2017 IEEE International Conference on Computer Vision (ICCV), pp. 1491\u20131500. IEEE (2017)","DOI":"10.1109\/ICCV.2017.165"},{"key":"15_CR40","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1007\/978-3-030-58545-7_19","volume-title":"Computer Vision \u2013 ECCV 2020","author":"T Park","year":"2020","unstructured":"Park, T., Efros, A.A., Zhang, R., Zhu, J.-Y.: Contrastive learning for unpaired image-to-image translation. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12354, pp. 319\u2013345. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58545-7_19"},{"key":"15_CR41","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\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2337\u20132346 (2019)","DOI":"10.1109\/CVPR.2019.00244"},{"key":"15_CR42","doi-asserted-by":"crossref","unstructured":"Parkhi, O., Vedaldi, A., Zisserman, A.: Deep face recognition. In: BMVC 2015-Proceedings of the British Machine Vision Conference 2015. British Machine Vision Association (2015)","DOI":"10.5244\/C.29.41"},{"key":"15_CR43","doi-asserted-by":"crossref","unstructured":"Pi, J., Zeng, J., Lu, Q., Jiang, N., Wu, H., Zeng, L., Wu, Z.: Adv-Eye: a transfer-based natural eye shadow attack on face recognition. IEEE Access (2023)","DOI":"10.1109\/ACCESS.2023.3307132"},{"key":"15_CR44","doi-asserted-by":"crossref","unstructured":"Poursaeed, O., Jiang, T., Yang, H., Belongie, S., Lim, S.N.: Robustness and generalization via generative adversarial training. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 15711\u201315720 (2021)","DOI":"10.1109\/ICCV48922.2021.01542"},{"key":"15_CR45","doi-asserted-by":"crossref","unstructured":"Qayyum, A., Ilahi, I., Shamshad, F., Boussaid, F., Bennamoun, M., Qadir, J.: Untrained neural network priors for inverse imaging problems: a survey. IEEE Transactions on Pattern Analysis and Machine Intelligence (2022)","DOI":"10.36227\/techrxiv.14208215.v1"},{"key":"15_CR46","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"636","DOI":"10.1007\/978-3-030-59722-1_61","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2020","author":"A Qayyum","year":"2020","unstructured":"Qayyum, A., Sultani, W., Shamshad, F., Qadir, J., Tufail, R.: Single-shot retinal image enhancement using deep image priors. In: Martel, A.L., et al. (eds.) MICCAI 2020. LNCS, vol. 12265, pp. 636\u2013646. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-59722-1_61"},{"key":"15_CR47","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2022.105879","volume":"148","author":"A Qayyum","year":"2022","unstructured":"Qayyum, A., Sultani, W., Shamshad, F., Tufail, R., Qadir, J.: Single-shot retinal image enhancement using untrained and pretrained neural networks priors integrated with analytical image priors. Comput. Biol. Med. 148, 105879 (2022)","journal-title":"Comput. Biol. Med."},{"issue":"3","key":"15_CR48","doi-asserted-by":"publisher","first-page":"375","DOI":"10.1177\/2032284420948161","volume":"11","author":"IN Rezende","year":"2020","unstructured":"Rezende, I.N.: Facial recognition in police hands: assessing the \u2018Clearview case\u2019 from a European perspective. N. J. Eur. Crim. Law 11(3), 375\u2013389 (2020)","journal-title":"N. J. Eur. Crim. Law"},{"key":"15_CR49","doi-asserted-by":"crossref","unstructured":"Schrader, K., Alt, T., Weickert, J., Ertel, M.: CNN-based Euler\u2019s Elastica inpainting with deep energy and deep image prior. In: 2022 10th European Workshop on Visual Information Processing (EUVIP), pp.\u00a01\u20136. IEEE (2022)","DOI":"10.1109\/EUVIP53989.2022.9922788"},{"key":"15_CR50","doi-asserted-by":"crossref","unstructured":"Schroff, F., Kalenichenko, D., Philbin, J.: FaceNet: a unified embedding for face recognition and clustering. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 815\u2013823 (2015)","DOI":"10.1109\/CVPR.2015.7298682"},{"key":"15_CR51","doi-asserted-by":"crossref","unstructured":"Shamshad, F., Abbas, F., Ahmed, A.: Deep Ptych: subsampled Fourier ptychography using generative priors. In: ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 7720\u20137724. IEEE (2019)","DOI":"10.1109\/ICASSP.2019.8682179"},{"key":"15_CR52","unstructured":"Shamshad, F., Ahmed, A.: Robust compressive phase retrieval via deep generative priors. arXiv preprint arXiv:1808.05854 (2018)"},{"key":"15_CR53","unstructured":"Shamshad, F., Ahmed, A.: Class-specific blind deconvolutional phase retrieval under a generative prior. arXiv preprint arXiv:2002.12578 (2020)"},{"issue":"2","key":"15_CR54","doi-asserted-by":"publisher","first-page":"2286","DOI":"10.1109\/JSEN.2020.3018751","volume":"21","author":"F Shamshad","year":"2020","unstructured":"Shamshad, F., Ahmed, A.: Compressed sensing-based robust phase retrieval via deep generative priors. IEEE Sens. J. 21(2), 2286\u20132298 (2020)","journal-title":"IEEE Sens. J."},{"key":"15_CR55","doi-asserted-by":"crossref","unstructured":"Shamshad, F., Hanif, A., Abbas, F., Awais, M., Ahmed, A.: Adaptive Ptych: leveraging image adaptive generative priors for subsampled Fourier ptychography. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision Workshops (2019)","DOI":"10.1109\/ICCVW.2019.00476"},{"key":"15_CR56","unstructured":"Shamshad, F., Hanif, A., Ahmed, A.: Subsampled fourier ptychography via pretrained invertible and untrained network priors. In: NeurIPS 2019 Workshop on Solving Inverse Problems with Deep Networks (2019)"},{"key":"15_CR57","doi-asserted-by":"crossref","unstructured":"Shamshad, F., Naseer, M., Nandakumar, K.: CLIP2Protect: protecting facial privacy using text-guided makeup via adversarial latent search. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 20595\u201320605 (2023)","DOI":"10.1109\/CVPR52729.2023.01973"},{"key":"15_CR58","doi-asserted-by":"crossref","unstructured":"Shamshad, F., Srivatsan, K., Nandakumar, K.: Evading forensic classifiers with attribute-conditioned adversarial faces. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 16469\u201316478 (2023)","DOI":"10.1109\/CVPR52729.2023.01580"},{"key":"15_CR59","unstructured":"Shan, S., Wenger, E., Zhang, J., Li, H., Zheng, H., Zhao, B.Y.: Fawkes: protecting privacy against unauthorized deep learning models. In: Proceedings of the 29th USENIX Security Symposium (USENIX Security\u201920), pp. 1589\u20131604 (2020)"},{"issue":"3","key":"15_CR60","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3317611","volume":"22","author":"M Sharif","year":"2019","unstructured":"Sharif, M., Bhagavatula, S., Bauer, L., Reiter, M.K.: A general framework for adversarial examples with objectives. ACM Trans. Priv. Secur. (TOPS) 22(3), 1\u201330 (2019)","journal-title":"ACM Trans. Priv. Secur. (TOPS)"},{"key":"15_CR61","unstructured":"Song, Y., Shu, R., Kushman, N., Ermon, S.: Constructing unrestricted adversarial examples with generative models. Adv. Neural Inf. Process. Syst. 31 (2018)"},{"key":"15_CR62","doi-asserted-by":"crossref","unstructured":"Sun, Y., Yu, L., Xie, H., Li, J., Zhang, Y.: DiffAM: diffusion-based adversarial makeup transfer for facial privacy protection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 24584\u201324594 (2024)","DOI":"10.1109\/CVPR52733.2024.02321"},{"key":"15_CR63","doi-asserted-by":"crossref","unstructured":"Tumanyan, N., Bar-Tal, O., Bagon, S., Dekel, T.: Splicing ViT features for semantic appearance transfer. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10748\u201310757 (2022)","DOI":"10.1109\/CVPR52688.2022.01048"},{"key":"15_CR64","doi-asserted-by":"crossref","unstructured":"Ulyanov, D., Vedaldi, A., Lempitsky, V.: Deep image prior. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 9446\u20139454 (2018)","DOI":"10.1109\/CVPR.2018.00984"},{"key":"15_CR65","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1016\/j.neucom.2020.10.081","volume":"429","author":"M Wang","year":"2021","unstructured":"Wang, M., Deng, W.: Deep face recognition: a survey. Neurocomputing 429, 215\u2013244 (2021)","journal-title":"Neurocomputing"},{"key":"15_CR66","doi-asserted-by":"crossref","unstructured":"Wang, Y., Bao, T., Ding, C., Zhu, M.: Face recognition in real-world surveillance videos with deep learning method. In: 2017 2nd International Conference on Image, Vision and Computing (ICIVC), pp. 239\u2013243. IEEE (2017)","DOI":"10.1109\/ICIVC.2017.7984553"},{"key":"15_CR67","unstructured":"Wenger, E., Shan, S., Zheng, H., Zhao, B.Y.: SoK: Anti-facial recognition technology. arXiv preprint arXiv:2112.04558 (2021)"},{"key":"15_CR68","doi-asserted-by":"crossref","unstructured":"Xia, W., Zhang, Y., Yang, Y., Xue, J.H., Zhou, B., Yang, M.H.: GAN inversion: a survey. IEEE Transactions on Pattern Analysis and Machine Intelligence (2022)","DOI":"10.1109\/TPAMI.2022.3181070"},{"key":"15_CR69","doi-asserted-by":"crossref","unstructured":"Xiao, Z., et al.: Improving transferability of adversarial patches on face recognition with generative models. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11845\u201311854 (2021)","DOI":"10.1109\/CVPR46437.2021.01167"},{"key":"15_CR70","doi-asserted-by":"crossref","unstructured":"Yang, X., et al.: Towards face encryption by generating adversarial identity masks. In: Proceedings of the 2021 IEEE\/CVF International Conference on Computer Vision (ICCV\u201921), pp. 3897\u20133907 (2021)","DOI":"10.1109\/ICCV48922.2021.00387"},{"key":"15_CR71","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"174","DOI":"10.1007\/978-3-030-58520-4_11","volume-title":"Computer Vision \u2013 ECCV 2020","author":"X Yang","year":"2020","unstructured":"Yang, X., Wei, F., Zhang, H., Zhu, J.: Design and interpretation of universal adversarial patches in face detection. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12362, pp. 174\u2013191. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58520-4_11"},{"key":"15_CR72","doi-asserted-by":"crossref","unstructured":"Yin, B., et al.: Adv-makeup: a new imperceptible and transferable attack on face recognition. In: Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI\u201921), pp. 1252\u20131258 (2021)","DOI":"10.24963\/ijcai.2021\/173"},{"key":"15_CR73","doi-asserted-by":"crossref","unstructured":"Yin, B., et al.: Adv-makeup: A new imperceptible and transferable attack on face recognition. arXiv preprint arXiv:2105.03162 (2021)","DOI":"10.24963\/ijcai.2021\/173"},{"key":"15_CR74","doi-asserted-by":"crossref","unstructured":"Yu, C., Wang, J., Peng, C., Gao, C., Yu, G., Sang, N.: BiSeNet: bilateral segmentation network for real-time semantic segmentation. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 325\u2013341 (2018)","DOI":"10.1007\/978-3-030-01261-8_20"},{"key":"15_CR75","unstructured":"Yuan, S., Zhang, Q., Gao, L., Cheng, Y., Song, J.: Natural color fool: Towards boosting black-box unrestricted attacks. arXiv preprint arXiv:2210.02041 (2022)"},{"issue":"10","key":"15_CR76","doi-asserted-by":"publisher","first-page":"1499","DOI":"10.1109\/LSP.2016.2603342","volume":"23","author":"K Zhang","year":"2016","unstructured":"Zhang, K., Zhang, Z., Li, Z., Qiao, Y.: Joint face detection and alignment using multitask cascaded convolutional networks. IEEE Signal Process. Lett. 23(10), 1499\u20131503 (2016)","journal-title":"IEEE Signal Process. Lett."},{"key":"15_CR77","doi-asserted-by":"crossref","unstructured":"Zhao, Z., Liu, Z., Larson, M.: Towards large yet imperceptible adversarial image perturbations with perceptual color distance. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 1039\u20131048 (2020)","DOI":"10.1109\/CVPR42600.2020.00112"},{"key":"15_CR78","doi-asserted-by":"crossref","unstructured":"Zhong, Y., Deng, W.: OPOM: customized invisible cloak towards face privacy protection. IEEE Transactions on Pattern Analysis and Machine Intelligence (2022)","DOI":"10.1109\/TPAMI.2022.3175602"},{"key":"15_CR79","doi-asserted-by":"crossref","unstructured":"Zhu, Z.A., Lu, Y.Z., Chiang, C.K.: Generating adversarial examples by makeup attacks on face recognition. In: 2019 IEEE International Conference on Image Processing (ICIP), pp. 2516\u20132520. IEEE (2019)","DOI":"10.1109\/ICIP.2019.8803269"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2024 Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-92089-9_15","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,24]],"date-time":"2025-05-24T12:49:15Z","timestamp":1748090955000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-92089-9_15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031920882","9783031920899"],"references-count":79,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-92089-9_15","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":"12 May 2025","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"}}]}}