{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T19:36:09Z","timestamp":1776886569159,"version":"3.51.2"},"publisher-location":"New York, NY, USA","reference-count":41,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,7,13]]},"DOI":"10.1145\/3726302.3729909","type":"proceedings-article","created":{"date-parts":[[2025,7,14]],"date-time":"2025-07-14T01:18:36Z","timestamp":1752455916000},"page":"296-305","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Brain Image Reconstruction with Retrieval-Augmented Diffusion"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-7167-282X","authenticated-orcid":false,"given":"Shuqi","family":"Zhu","sequence":"first","affiliation":[{"name":"Department of Computer Science and Technology, Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5622-0235","authenticated-orcid":false,"given":"Ziyi","family":"Ye","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-4498-1391","authenticated-orcid":false,"given":"Yi","family":"Zhong","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5030-709X","authenticated-orcid":false,"given":"Qingyao","family":"Ai","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Tsinghua University, Beijing, China and Zhongguancun Laboratory, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3530-3787","authenticated-orcid":false,"given":"Yujia","family":"Zhou","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0140-4512","authenticated-orcid":false,"given":"Yiqun","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Tsinghua University, Beijing, China and Zhongguancun Laboratory, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2025,7,13]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"crossref","unstructured":"Emily J Allen Ghislain St-Yves Yihan Wu Jesse L Breedlove Jacob S Prince Logan T Dowdle Matthias Nau Brad Caron Franco Pestilli Ian Charest et al. 2022. A massive 7T fMRI dataset to bridge cognitive neuroscience and artificial intelligence. Nature neuroscience Vol. 25 1 (2022) 116--126.","DOI":"10.1038\/s41593-021-00962-x"},{"key":"e_1_3_2_1_2_1","volume-title":"DreamDiffusion: High-Quality EEG-to-Image Generation with Temporal Masked Signal Modeling and CLIP Alignment. In European Conference on Computer Vision. Springer, 472--488","author":"Bai Yunpeng","year":"2025","unstructured":"Yunpeng Bai, Xintao Wang, Yan-Pei Cao, Yixiao Ge, Chun Yuan, and Ying Shan. 2025. DreamDiffusion: High-Quality EEG-to-Image Generation with Temporal Masked Signal Modeling and CLIP Alignment. In European Conference on Computer Vision. Springer, 472--488."},{"key":"e_1_3_2_1_3_1","volume-title":"Brain decoding: toward real-time reconstruction of visual perception. arXiv preprint arXiv:2310.19812","author":"Benchetrit Yohann","year":"2023","unstructured":"Yohann Benchetrit, Hubert Banville, and Jean-R\u00e9mi King. 2023. Brain decoding: toward real-time reconstruction of visual perception. arXiv preprint arXiv:2310.19812 (2023)."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tics.2021.07.006"},{"key":"e_1_3_2_1_5_1","first-page":"15309","article-title":"Retrieval-augmented diffusion models","volume":"35","author":"Blattmann Andreas","year":"2022","unstructured":"Andreas Blattmann, Robin Rombach, Kaan Oktay, Jonas M\u00fcller, and Bj\u00f6rn Ommer. 2022. Retrieval-augmented diffusion models. Advances in Neural Information Processing Systems, Vol. 35 (2022), 15309--15324.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_6_1","volume-title":"Unsupervised learning of visual features by contrasting cluster assignments. Advances in neural information processing systems","author":"Caron Mathilde","year":"2020","unstructured":"Mathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, and Armand Joulin. 2020. Unsupervised learning of visual features by contrasting cluster assignments. Advances in neural information processing systems, Vol. 33 (2020), 9912--9924."},{"key":"e_1_3_2_1_7_1","unstructured":"Alexandre D'Efossez C. Caucheteux J. Rapin Ori Kabeli and J. King. 2022. Decoding speech from non-invasive brain recordings. ArXiv Vol. abs\/2208.12266 (2022)."},{"key":"e_1_3_2_1_8_1","volume-title":"Diffusion models beat gans on image synthesis. Advances in neural information processing systems","author":"Dhariwal Prafulla","year":"2021","unstructured":"Prafulla Dhariwal and Alexander Nichol. 2021. Diffusion models beat gans on image synthesis. Advances in neural information processing systems, Vol. 34 (2021), 8780--8794."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/NER.2013.6695876"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2022.119754"},{"key":"e_1_3_2_1_11_1","volume-title":"Decoding natural image stimuli from fmri data with a surface-based convolutional network. arXiv preprint arXiv:2212.02409","author":"Gu Zijin","year":"2022","unstructured":"Zijin Gu, Keith Jamison, Amy Kuceyeski, and Mert Sabuncu. 2022. Decoding natural image stimuli from fmri data with a surface-based convolutional network. arXiv preprint arXiv:2212.02409 (2022)."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.7554\/eLife.82580"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0223792"},{"key":"e_1_3_2_1_14_1","volume-title":"Choo Min Lim, and PK Sadasivan","author":"Kannathal N","year":"2005","unstructured":"N Kannathal, U Rajendra Acharya, Choo Min Lim, and PK Sadasivan. 2005. Characterization of EEG-a comparative study. Computer methods and Programs in Biomedicine, Vol. 80, 1 (2005), 17--23."},{"key":"e_1_3_2_1_15_1","volume-title":"Imagenet classification with deep convolutional neural networks. Advances in neural information processing systems","author":"Krizhevsky Alex","year":"2012","unstructured":"Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. 2012. Imagenet classification with deep convolutional neural networks. Advances in neural information processing systems, Vol. 25 (2012)."},{"key":"e_1_3_2_1_16_1","volume-title":"Visual decoding and reconstruction via eeg embeddings with guided diffusion. arXiv preprint arXiv:2403.07721","author":"Li Dongyang","year":"2024","unstructured":"Dongyang Li, Chen Wei, Shiying Li, Jiachen Zou, Haoyang Qin, and Quanying Liu. 2024. Visual decoding and reconstruction via eeg embeddings with guided diffusion. arXiv preprint arXiv:2403.07721 (2024)."},{"key":"e_1_3_2_1_17_1","volume-title":"Sdedit: Guided image synthesis and editing with stochastic differential equations. arXiv preprint arXiv:2108.01073","author":"Meng Chenlin","year":"2021","unstructured":"Chenlin Meng, Yutong He, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, and Stefano Ermon. 2021. Sdedit: Guided image synthesis and editing with stochastic differential equations. arXiv preprint arXiv:2108.01073 (2021)."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-022-08178-1"},{"key":"e_1_3_2_1_19_1","volume-title":"Representation learning with contrastive predictive coding. arXiv preprint arXiv:1807.03748","author":"van den Oord Aaron","year":"2018","unstructured":"Aaron van den Oord, Yazhe Li, and Oriol Vinyals. 2018. Representation learning with contrastive predictive coding. arXiv preprint arXiv:1807.03748 (2018)."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-023-42891-8"},{"key":"e_1_3_2_1_21_1","volume-title":"International conference on machine learning. PMLR, 8748--8763","author":"Radford Alec","year":"2021","unstructured":"Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al. 2021. Learning transferable visual models from natural language supervision. In International conference on machine learning. PMLR, 8748--8763."},{"key":"e_1_3_2_1_22_1","volume-title":"Imagenet-21k pretraining for the masses. arXiv preprint arXiv:2104.10972","author":"Ridnik Tal","year":"2021","unstructured":"Tal Ridnik, Emanuel Ben-Baruch, Asaf Noy, and Lihi Zelnik-Manor. 2021. Imagenet-21k pretraining for the masses. arXiv preprint arXiv:2104.10972 (2021)."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"e_1_3_2_1_24_1","volume-title":"U-net: Convolutional networks for biomedical image segmentation. In Medical image computing and computer-assisted intervention--MICCAI 2015: 18th international conference","author":"Ronneberger Olaf","year":"2015","unstructured":"Olaf Ronneberger, Philipp Fischer, and Thomas Brox. 2015. U-net: Convolutional networks for biomedical image segmentation. In Medical image computing and computer-assisted intervention--MICCAI 2015: 18th international conference, Munich, Germany, October 5--9, 2015, proceedings, part III 18. Springer, 234--241."},{"key":"e_1_3_2_1_25_1","volume-title":"Advances in Neural Information Processing Systems","volume":"36","author":"Scotti Paul","year":"2024","unstructured":"Paul Scotti, Atmadeep Banerjee, Jimmie Goode, Stepan Shabalin, Alex Nguyen, Aidan Dempster, Nathalie Verlinde, Elad Yundler, David Weisberg, Kenneth Norman, et al. 2024a. Reconstructing the mind's eye: fMRI-to-image with contrastive learning and diffusion priors. Advances in Neural Information Processing Systems, Vol. 36 (2024)."},{"key":"e_1_3_2_1_26_1","volume-title":"Reese Kneeland, Tong Chen, Ashutosh Narang, Charan Santhirasegaran, Jonathan Xu, Thomas Naselaris, Kenneth A Norman, et al.","author":"Scotti Paul S","year":"2024","unstructured":"Paul S Scotti, Mihir Tripathy, Cesar Kadir Torrico Villanueva, Reese Kneeland, Tong Chen, Ashutosh Narang, Charan Santhirasegaran, Jonathan Xu, Thomas Naselaris, Kenneth A Norman, et al. 2024b. MindEye2: Shared-Subject Models Enable fMRI-To-Image With 1 Hour of Data. arXiv preprint arXiv:2403.11207 (2024)."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/WACV57701.2024.00738"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP49357.2023.10096587"},{"key":"e_1_3_2_1_29_1","volume-title":"Decoding Natural Images from EEG for Object Recognition. arXiv preprint arXiv:2308.13234","author":"Song Yonghao","year":"2023","unstructured":"Yonghao Song, Bingchuan Liu, Xiang Li, Nanlin Shi, Yijun Wang, and Xiaorong Gao. 2023. Decoding Natural Images from EEG for Object Recognition. arXiv preprint arXiv:2308.13234 (2023)."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01389"},{"key":"e_1_3_2_1_32_1","volume-title":"International conference on machine learning. PMLR, 6105--6114","author":"Tan Mingxing","year":"2019","unstructured":"Mingxing Tan and Quoc Le. 2019. Efficientnet: Rethinking model scaling for convolutional neural networks. In International conference on machine learning. PMLR, 6105--6114."},{"key":"e_1_3_2_1_33_1","volume-title":"Visual working memory directly alters perception. Nature human behaviour","author":"Teng Chunyue","year":"2019","unstructured":"Chunyue Teng and Dwight J Kravitz. 2019. Visual working memory directly alters perception. Nature human behaviour, Vol. 3, 8 (2019), 827--836."},{"key":"e_1_3_2_1_34_1","unstructured":"Michal Teplan et al. 2002. Fundamentals of EEG measurement. Measurement science review Vol. 2 2 (2002) 1--11."},{"key":"e_1_3_2_1_35_1","volume-title":"Image quality assessment: from error visibility to structural similarity","author":"Wang Zhou","year":"2004","unstructured":"Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli. 2004. Image quality assessment: from error visibility to structural similarity. IEEE transactions on image processing, Vol. 13, 4 (2004), 600--612."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3664647.3681296"},{"key":"e_1_3_2_1_37_1","volume-title":"Maria L Bringas Vega, and Pedro A Vald\u00e9s Sosa","author":"Yao Dezhong","year":"2019","unstructured":"Dezhong Yao, Yun Qin, Shiang Hu, Li Dong, Maria L Bringas Vega, and Pedro A Vald\u00e9s Sosa. 2019. Which reference should we use for EEG and ERP practice? Brain topography, Vol. 32 (2019), 530--549."},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3637874"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2023.105125"},{"key":"e_1_3_2_1_40_1","volume-title":"EEG-SVRec: An EEG Dataset with User Multidimensional Affective Engagement Labels in Short Video Recommendation. arXiv preprint arXiv:2404.01008","author":"Zhang Shaorun","year":"2024","unstructured":"Shaorun Zhang, Zhiyu He, Ziyi Ye, Peijie Sun, Qingyao Ai, Min Zhang, and Yiqun Liu. 2024. EEG-SVRec: An EEG Dataset with User Multidimensional Affective Engagement Labels in Short Video Recommendation. arXiv preprint arXiv:2404.01008 (2024)."},{"key":"e_1_3_2_1_41_1","volume-title":"EEG-ImageNet: An Electroencephalogram Dataset and Benchmarks with Image Visual Stimuli of Multi-Granularity Labels. arXiv preprint arXiv:2406.07151","author":"Zhu Shuqi","year":"2024","unstructured":"Shuqi Zhu, Ziyi Ye, Qingyao Ai, and Yiqun Liu. 2024. EEG-ImageNet: An Electroencephalogram Dataset and Benchmarks with Image Visual Stimuli of Multi-Granularity Labels. arXiv preprint arXiv:2406.07151 (2024)."}],"event":{"name":"SIGIR '25: The 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","location":"Padua Italy","acronym":"SIGIR '25","sponsor":["SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3726302.3729909","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T18:29:20Z","timestamp":1755887360000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3726302.3729909"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,13]]},"references-count":41,"alternative-id":["10.1145\/3726302.3729909","10.1145\/3726302"],"URL":"https:\/\/doi.org\/10.1145\/3726302.3729909","relation":{},"subject":[],"published":{"date-parts":[[2025,7,13]]},"assertion":[{"value":"2025-07-13","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}