{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T20:25:20Z","timestamp":1769631920856,"version":"3.49.0"},"publisher-location":"New York, NY, USA","reference-count":63,"publisher":"ACM","funder":[{"DOI":"10.13039\/501100003977","name":"Israel Science Foundation","doi-asserted-by":"publisher","award":["951\/24, 409\/24"],"award-info":[{"award-number":["951\/24, 409\/24"]}],"id":[{"id":"10.13039\/501100003977","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,12,15]]},"DOI":"10.1145\/3757377.3763969","type":"proceedings-article","created":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T16:30:41Z","timestamp":1765211441000},"page":"1-12","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["ELAD: Blind Face Restoration using Expectation-based Likelihood Approximation and Diffusion Prior"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-0174-4008","authenticated-orcid":false,"given":"Sean","family":"Man","sequence":"first","affiliation":[{"name":"Technion- Israel Institute of Technology, Haifa, Israel"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-5112-6558","authenticated-orcid":false,"given":"Guy","family":"Ohayon","sequence":"additional","affiliation":[{"name":"Technion - Israel Institute of Technology, Haifa, Israel"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-8169-4399","authenticated-orcid":false,"given":"Ron","family":"Raphaeli","sequence":"additional","affiliation":[{"name":"Technion - Israel Institute of Technology, Haifa, Israel"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-2621-5286","authenticated-orcid":false,"given":"Matan","family":"Kleiner","sequence":"additional","affiliation":[{"name":"Technion - Israel Institute of Technology, Haifa, Israel"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8131-6928","authenticated-orcid":false,"given":"Michael","family":"Elad","sequence":"additional","affiliation":[{"name":"Technion - Israel Institute of Technology, Haifa, Israel and NVIDIA, Haifa, Israel"}]}],"member":"320","published-online":{"date-parts":[[2025,12,14]]},"reference":[{"key":"e_1_3_3_3_2_1","unstructured":"Sefi Bell-Kligler Assaf Shocher and Michal Irani. 2019. Blind super-resolution kernel estimation using an internal-gan. Advances in Neural Information Processing Systems 32 (2019)."},{"key":"e_1_3_3_3_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00652"},{"key":"e_1_3_3_3_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01129"},{"key":"e_1_3_3_3_5_1","unstructured":"Jin Cao Deyu Meng and Xiangyong Cao. 2024. Chain-of-Restoration: Multi-Task Image Restoration Models Are Zero-Shot Step-by-Step Universal Image Restorers. arXiv:2410.08688 (Oct. 2024). arxiv:https:\/\/arXiv.org\/abs\/2410.08688"},{"key":"e_1_3_3_3_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00587"},{"key":"e_1_3_3_3_7_1","volume-title":"The Eleventh International Conference on Learning Representations","author":"Chung Hyungjin","year":"2022","unstructured":"Hyungjin Chung, Jeongsol Kim, Michael\u00a0Thompson Mccann, Marc\u00a0Louis Klasky, and Jong\u00a0Chul Ye. 2022. Diffusion Posterior Sampling for General Noisy Inverse Problems. In The Eleventh International Conference on Learning Representations."},{"key":"e_1_3_3_3_8_1","unstructured":"Noa Cohen Hila Manor Yuval Bahat and Tomer Michaeli. 2023. From Posterior Sampling to Meaningful Diversity in Image Restoration. https:\/\/openreview.net\/forum?id=ff2g30cZxj"},{"key":"e_1_3_3_3_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00482"},{"key":"e_1_3_3_3_10_1","doi-asserted-by":"crossref","unstructured":"Bradley Efron. 2011. Tweedie\u2019s Formula and Selection Bias. J. Amer. Statist. Assoc. 106 496 (2011) 1602\u20131614. jstor:23239562","DOI":"10.1198\/jasa.2011.tm11181"},{"key":"e_1_3_3_3_11_1","unstructured":"SG161222 Evgeny. 2023. Stablediffusionapi\/Realistic-Vision-51 \u00b7 Hugging Face. https:\/\/huggingface.co\/stablediffusionapi\/realistic-vision-51."},{"key":"e_1_3_3_3_12_1","first-page":"25661","volume-title":"Advances in Neural Information Processing Systems","author":"Freirich Dror","year":"2021","unstructured":"Dror Freirich, Tomer Michaeli, and Ron Meir. 2021. A Theory of the Distortion-Perception Tradeoff in Wasserstein Space. In Advances in Neural Information Processing Systems , Vol.\u00a034. Curran Associates, Inc., 25661\u201325672."},{"key":"e_1_3_3_3_13_1","volume-title":"Advances in Neural Information Processing Systems","author":"Goodfellow Ian","year":"2014","unstructured":"Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014. Generative Adversarial Nets. In Advances in Neural Information Processing Systems , Vol.\u00a027. Curran Associates, Inc.https:\/\/proceedings.neurips.cc\/paper\/2014\/hash\/5ca3e9b122f61f8f06494c97b1afccf3-Abstract.html"},{"key":"e_1_3_3_3_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19797-0_8"},{"key":"e_1_3_3_3_15_1","volume-title":"Advances in Neural Information Processing Systems","author":"Heusel Martin","year":"2017","unstructured":"Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter. 2017. GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium. In Advances in Neural Information Processing Systems , Vol.\u00a030. Curran Associates, Inc."},{"key":"e_1_3_3_3_16_1","first-page":"6840","volume-title":"Advances in Neural Information Processing Systems","author":"Ho Jonathan","year":"2020","unstructured":"Jonathan Ho, Ajay Jain, and Pieter Abbeel. 2020. Denoising Diffusion Probabilistic Models. In Advances in Neural Information Processing Systems , Vol.\u00a033. Curran Associates, Inc., 6840\u20136851."},{"key":"e_1_3_3_3_17_1","volume-title":"Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments","author":"Huang Gary\u00a0B.","year":"2007","unstructured":"Gary\u00a0B. Huang, Manu Ramesh, Tamara Berg, and Erik Learned-Miller. 2007. Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments. Technical Report 07-49. University of Massachusetts, Amherst."},{"key":"e_1_3_3_3_18_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-33720-9_44"},{"key":"e_1_3_3_3_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW50498.2020.00241"},{"key":"e_1_3_3_3_20_1","doi-asserted-by":"crossref","unstructured":"Aiwen Jiang Zhi Wei Long Peng Feiqiang Liu Wenbo Li and Mingwen Wang. 2024. DaLPSR: Leverage Degradation-Aligned Language Prompt for Real-World Image Super-Resolution. arXiv:2406.16477 (June 2024). arxiv:https:\/\/arXiv.org\/abs\/2406.16477\u00a0[cs]","DOI":"10.2139\/ssrn.5295734"},{"key":"e_1_3_3_3_21_1","volume-title":"International Conference on Learning Representations","author":"Karras Tero","year":"2018","unstructured":"Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen. 2018. Progressive Growing of GANs for Improved Quality, Stability, and Variation. In International Conference on Learning Representations."},{"key":"e_1_3_3_3_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00453"},{"key":"e_1_3_3_3_23_1","unstructured":"Bahjat Kawar Michael Elad Stefano Ermon and Jiaming Song. 2022. Denoising Diffusion Restoration Models. Advances in Neural Information Processing Systems 35 (Dec. 2022) 23593\u201323606."},{"key":"e_1_3_3_3_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/WACV57701.2024.00519"},{"key":"e_1_3_3_3_25_1","unstructured":"Senmao Li Kai Wang Joost van\u00a0de Weijer Fahad\u00a0Shahbaz Khan Chun-Le Guo Shiqi Yang Yaxing Wang Jian Yang and Ming-Ming Cheng. 2024. $InterLCM$: Low-Quality Images as Intermediate States of Latent Consistency Models for Effective Blind Face Restoration. https:\/\/openreview.net\/forum?id=rUxr9Ll5FQ"},{"key":"e_1_3_3_3_26_1","doi-asserted-by":"crossref","unstructured":"Xinqi Lin Jingwen He Ziyan Chen Zhaoyang Lyu Bo Dai Fanghua Yu Wanli Ouyang Yu Qiao and Chao Dong. 2024. DiffBIR: Towards Blind Image Restoration with Generative Diffusion Prior. arXiv:2308.15070 (April 2024). arxiv:https:\/\/arXiv.org\/abs\/2308.15070\u00a0[cs]","DOI":"10.1007\/978-3-031-73202-7_25"},{"key":"e_1_3_3_3_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.425"},{"key":"e_1_3_3_3_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW59228.2023.00134"},{"key":"e_1_3_3_3_29_1","unstructured":"Hila Manor and Tomer Michaeli. 2023. On the Posterior Distribution in Denoising: Application to Uncertainty Quantification. https:\/\/openreview.net\/forum?id=adSGeugiuj"},{"key":"e_1_3_3_3_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.121"},{"key":"e_1_3_3_3_31_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10578-9_51"},{"key":"e_1_3_3_3_32_1","unstructured":"Koichi Miyasawa et\u00a0al. 1961. An empirical Bayes estimator of the mean of a normal population. Bull. Inst. Internat. Statist 38 181-188 (1961) 1\u20132."},{"key":"e_1_3_3_3_33_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19790-1_43"},{"key":"e_1_3_3_3_34_1","first-page":"25501","volume-title":"Proceedings of the 40th International Conference on Machine Learning","author":"Murata Naoki","year":"2023","unstructured":"Naoki Murata, Koichi Saito, Chieh-Hsin Lai, Yuhta Takida, Toshimitsu Uesaka, Yuki Mitsufuji, and Stefano Ermon. 2023. GibbsDDRM: A Partially Collapsed Gibbs Sampler for Solving Blind Inverse Problems with Denoising Diffusion Restoration. In Proceedings of the 40th International Conference on Machine Learning. PMLR, 25501\u201325522."},{"key":"e_1_3_3_3_35_1","doi-asserted-by":"publisher","unstructured":"Elias Nehme and Tomer Michaeli. 2025. Generative AI for Solving Inverse Problems in Computational Imaging. XRDS 31 2 (Jan. 2025) 32\u201337. 10.1145\/3703401","DOI":"10.1145\/3703401"},{"key":"e_1_3_3_3_36_1","doi-asserted-by":"crossref","unstructured":"Elias Nehme Rotem Mulayoff and Tomer Michaeli. 2024. Hierarchical Uncertainty Exploration via Feedforward Posterior Trees. Advances in Neural Information Processing Systems 37 (Dec. 2024) 125142\u2013125191. https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2024\/hash\/e262fc23ec7275230ee77c55d0cc9555-Abstract-Conference.html","DOI":"10.52202\/079017-3975"},{"key":"e_1_3_3_3_37_1","unstructured":"Elias Nehme Omer Yair and Tomer Michaeli. 2023. Uncertainty Quantification via Neural Posterior Principal Components. Advances in Neural Information Processing Systems 36 (Dec. 2023) 37128\u201337141. https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2023\/hash\/74fc5575632191d96881d8015f79dde3-Abstract-Conference.html"},{"key":"e_1_3_3_3_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW54120.2021.00207"},{"key":"e_1_3_3_3_39_1","first-page":"26474","volume-title":"Proceedings of the 40th International Conference on Machine Learning","author":"Ohayon Guy","year":"2023","unstructured":"Guy Ohayon, Theo\u00a0Joseph Adrai, Michael Elad, and Tomer Michaeli. 2023. Reasons for the Superiority of Stochastic Estimators over Deterministic Ones: Robustness, Consistency and Perceptual Quality. In Proceedings of the 40th International Conference on Machine Learning. PMLR, 26474\u201326494."},{"key":"e_1_3_3_3_40_1","unstructured":"Guy Ohayon Tomer Michaeli and Michael Elad. 2024. Posterior-Mean Rectified Flow: Towards Minimum MSE Photo-Realistic Image Restoration. arXiv:2410.00418 (Oct. 2024). arxiv:https:\/\/arXiv.org\/abs\/2410.00418"},{"key":"e_1_3_3_3_41_1","unstructured":"Maxime Oquab Timoth\u00e9e Darcet Th\u00e9o Moutakanni Huy Vo Marc Szafraniec Vasil Khalidov Pierre Fernandez Daniel Haziza Francisco Massa Alaaeldin El-Nouby Mahmoud Assran Nicolas Ballas Wojciech Galuba Russell Howes Po-Yao Huang Shang-Wen Li Ishan Misra Michael Rabbat Vasu Sharma Gabriel Synnaeve Hu Xu Herv\u00e9 Jegou Julien Mairal Patrick Labatut Armand Joulin and Piotr Bojanowski. 2024. DINOv2: Learning Robust Visual Features without Supervision. arxiv:https:\/\/arXiv.org\/abs\/2304.07193\u00a0[cs]"},{"key":"e_1_3_3_3_42_1","unstructured":"Ron Raphaeli Sean Man and Michael Elad. 2025. SILO: Solving Inverse Problems with Latent Operators. arxiv:https:\/\/arXiv.org\/abs\/2501.11746\u00a0[cs]"},{"key":"e_1_3_3_3_43_1","unstructured":"Mengwei Ren Mauricio Delbracio Hossein Talebi Guido Gerig and Peyman Milanfar. 2023. Multiscale Structure Guided Diffusion for Image Deblurring. 10721\u201310733. https:\/\/openaccess.thecvf.com\/content\/ICCV2023\/html\/Ren_Multiscale_Structure_Guided_Diffusion_for_Image_Deblurring_ICCV_2023_paper.html"},{"key":"e_1_3_3_3_44_1","doi-asserted-by":"publisher","DOI":"10.1525\/9780520313880-015"},{"key":"e_1_3_3_3_45_1","doi-asserted-by":"crossref","unstructured":"Robin Rombach Andreas Blattmann Dominik Lorenz Patrick Esser and Bj\u00f6rn Ommer. 2022. High-Resolution Image Synthesis With Latent Diffusion Models. 10684\u201310695. https:\/\/openaccess.thecvf.com\/content\/CVPR2022\/html\/Rombach_High-Resolution_Image_Synthesis_With_Latent_Diffusion_Models_CVPR_2022_paper","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"e_1_3_3_3_46_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW56347.2022.00095"},{"key":"e_1_3_3_3_47_1","doi-asserted-by":"publisher","DOI":"10.1145\/3528233.3530757"},{"key":"e_1_3_3_3_48_1","first-page":"2256","volume-title":"Proceedings of the 32nd International Conference on Machine Learning","author":"Sohl-Dickstein Jascha","year":"2015","unstructured":"Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli. 2015. Deep Unsupervised Learning Using Nonequilibrium Thermodynamics. In Proceedings of the 32nd International Conference on Machine Learning. PMLR, 2256\u20132265."},{"key":"e_1_3_3_3_49_1","volume-title":"International Conference on Learning Representations","author":"Song Jiaming","year":"2020","unstructured":"Jiaming Song, Chenlin Meng, and Stefano Ermon. 2020. Denoising Diffusion Implicit Models. In International Conference on Learning Representations."},{"key":"e_1_3_3_3_50_1","volume-title":"International Conference on Learning Representations","author":"Song Jiaming","year":"2022","unstructured":"Jiaming Song, Arash Vahdat, Morteza Mardani, and Jan Kautz. 2022. Pseudoinverse-Guided Diffusion Models for Inverse Problems. In International Conference on Learning Representations."},{"key":"e_1_3_3_3_51_1","doi-asserted-by":"crossref","unstructured":"Charles\u00a0M Stein. 1981. Estimation of the mean of a multivariate normal distribution. The annals of Statistics (1981) 1135\u20131151.","DOI":"10.1214\/aos\/1176345632"},{"key":"e_1_3_3_3_52_1","unstructured":"George Stein Jesse Cresswell Rasa Hosseinzadeh Yi Sui Brendan Ross Valentin Villecroze Zhaoyan Liu Anthony\u00a0L. Caterini Eric Taylor and Gabriel Loaiza-Ganem. 2023. Exposing Flaws of Generative Model Evaluation Metrics and Their Unfair Treatment of Diffusion Models. Advances in Neural Information Processing Systems 36 (Dec. 2023) 3732\u20133784."},{"key":"e_1_3_3_3_53_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"key":"e_1_3_3_3_54_1","doi-asserted-by":"crossref","unstructured":"Phong Tran Anh Tran Quynh Phung and Minh Hoai. 2021. Explore Image Deblurring via Blur Kernel Space. arXiv:2104.00317 (April 2021). arxiv:https:\/\/arXiv.org\/abs\/2104.00317","DOI":"10.1109\/CVPR46437.2021.01178"},{"key":"e_1_3_3_3_55_1","unstructured":"Siwei Tu Weidong Yang and Ben Fei. 2024. Taming Generative Diffusion for Universal Blind Image Restoration. arXiv:2408.11287 (Aug. 2024). arxiv:https:\/\/arXiv.org\/abs\/2408.11287\u00a0[cs]"},{"key":"e_1_3_3_3_56_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00905"},{"key":"e_1_3_3_3_57_1","doi-asserted-by":"crossref","unstructured":"Zhouxia Wang Jiawei Zhang Tianshui Chen Wenping Wang and Ping Luo. 2023a. RestoreFormer++: Towards Real-World Blind Face Restoration From Undegraded Key-Value Pairs. IEEE Transactions on Pattern Analysis and Machine Intelligence 45 12 (Dec. 2023) 15462\u201315476.","DOI":"10.1109\/TPAMI.2023.3315753"},{"key":"e_1_3_3_3_58_1","doi-asserted-by":"crossref","unstructured":"Zhixin Wang Ziying Zhang Xiaoyun Zhang Huangjie Zheng Mingyuan Zhou Ya Zhang and Yanfeng Wang. 2023b. DR2: Diffusion-Based Robust Degradation Remover for Blind Face Restoration. 1704\u20131713. https:\/\/openaccess.thecvf.com\/content\/CVPR2023\/html\/Wang_DR2_Diffusion-Based_Robust_Degradation_Remover_for_Blind_Face_Restoration_CVPR_2023_paper.html","DOI":"10.1109\/CVPR52729.2023.00170"},{"key":"e_1_3_3_3_59_1","doi-asserted-by":"crossref","unstructured":"Jay Whang Mauricio Delbracio Hossein Talebi Chitwan Saharia Alexandros\u00a0G. Dimakis and Peyman Milanfar. 2022. Deblurring via Stochastic Refinement. 16293\u201316303. https:\/\/openaccess.thecvf.com\/content\/CVPR2022\/html\/Whang_Deblurring_via_Stochastic_Refinement_CVPR_2022_paper.html","DOI":"10.1109\/CVPR52688.2022.01581"},{"key":"e_1_3_3_3_60_1","unstructured":"Peiqing Yang Shangchen Zhou Qingyi Tao and Chen\u00a0Change Loy. 2023. PGDiff: Guiding Diffusion Models for Versatile Face Restoration via Partial Guidance. Advances in Neural Information Processing Systems 36 (Dec. 2023) 32194\u201332214."},{"key":"e_1_3_3_3_61_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.596"},{"key":"e_1_3_3_3_62_1","unstructured":"Zongsheng Yue and Chen\u00a0Change Loy. 2023. DifFace: Blind Face Restoration with Diffused Error Contraction. arXiv:2212.06512 (Dec. 2023). arxiv:https:\/\/arXiv.org\/abs\/2212.06512\u00a0[cs]"},{"key":"e_1_3_3_3_63_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00068"},{"key":"e_1_3_3_3_64_1","unstructured":"Shangchen Zhou Kelvin Chan Chongyi Li and Chen\u00a0Change Loy. 2022. Towards Robust Blind Face Restoration with Codebook Lookup Transformer. Advances in Neural Information Processing Systems 35 (Dec. 2022) 30599\u201330611."}],"event":{"name":"SA Conference Papers '25: SIGGRAPH Asia 2025 Conference Papers","location":"Hong Kong Hong Kong","acronym":"SA Conference Papers '25","sponsor":["SIGGRAPH ACM Special Interest Group on Computer Graphics and Interactive Techniques"]},"container-title":["Proceedings of the SIGGRAPH Asia 2025 Conference Papers"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3757377.3763969","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T03:27:52Z","timestamp":1765250872000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3757377.3763969"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,14]]},"references-count":63,"alternative-id":["10.1145\/3757377.3763969","10.1145\/3757377"],"URL":"https:\/\/doi.org\/10.1145\/3757377.3763969","relation":{},"subject":[],"published":{"date-parts":[[2025,12,14]]},"assertion":[{"value":"2025-12-14","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}