{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T06:07:14Z","timestamp":1773900434886,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":76,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,10,26]],"date-time":"2023-10-26T00:00:00Z","timestamp":1698278400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62072271"],"award-info":[{"award-number":["62072271"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,10,26]]},"DOI":"10.1145\/3581783.3611917","type":"proceedings-article","created":{"date-parts":[[2023,10,27]],"date-time":"2023-10-27T07:27:40Z","timestamp":1698391660000},"page":"676-687","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Blind Image Super-resolution with Rich Texture-Aware Codebook"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5901-9775","authenticated-orcid":false,"given":"Rui","family":"Qin","sequence":"first","affiliation":[{"name":"Tsinghua University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5948-2708","authenticated-orcid":false,"given":"Ming","family":"Sun","sequence":"additional","affiliation":[{"name":"Kuaishou Technology, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6698-5656","authenticated-orcid":false,"given":"Fangyuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijng, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-2657-8828","authenticated-orcid":false,"given":"Xing","family":"Wen","sequence":"additional","affiliation":[{"name":"Kuaishou Technology, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5176-9202","authenticated-orcid":false,"given":"Bin","family":"Wang","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2023,10,27]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.150"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"crossref","unstructured":"Marco Bevilacqua Aline Roumy Christine Guillemot and Marie Line Alberi-Morel. 2012. Low-complexity single-image super-resolution based on nonnegative neighbor embedding. (2012).","DOI":"10.5244\/C.26.135"},{"key":"e_1_3_2_1_3_1","volume-title":"Large scale GAN training for high fidelity natural image synthesis. arXiv preprint arXiv:1809.11096","author":"Brock Andrew","year":"2018","unstructured":"Andrew Brock, Jeff Donahue, and Karen Simonyan. 2018. Large scale GAN training for high fidelity natural image synthesis. arXiv preprint arXiv:1809.11096 (2018)."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01402"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2004.1315043"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2020.3043093"},{"key":"e_1_3_2_1_7_1","volume-title":"Blind Image Super Resolution with Semantic-Aware Quantized Texture Prior. arXiv preprint arXiv:2202.13142","author":"Chen Chaofeng","year":"2022","unstructured":"Chaofeng Chen, Xinyu Shi, Yipeng Qin, Xiaoming Li, Xiaoguang Han, Tao Yang, and Shihui Guo. 2022a. Blind Image Super Resolution with Semantic-Aware Quantized Texture Prior. arXiv preprint arXiv:2202.13142 (2022)."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3547833"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01212"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.2994150"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10593-2_13"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01268"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19800-7_14"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00308"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2019.00435"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00195"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00502"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.266"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7299156"},{"key":"e_1_3_2_1_21_1","first-page":"5632","article-title":"Unfolding the alternating optimization for blind super resolution","volume":"33","author":"Huang Yan","year":"2020","unstructured":"Yan Huang, Shang Li, Liang Wang, Tieniu Tan, et al. 2020. Unfolding the alternating optimization for blind super resolution. Advances in Neural Information Processing Systems, Vol. 33 (2020), 5632--5643.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00214"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46475-6_43"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00813"},{"key":"e_1_3_2_1_25_1","volume-title":"Computer Graphics Forum","author":"Kim Beomseok","unstructured":"Beomseok Kim, Hyeongseok Son, Seong-Jin Park, Sunghyun Cho, and Seungyong Lee. 2018. Defocus and motion blur detection with deep contextual features. In Computer Graphics Forum, Vol. 37. Wiley Online Library, 277--288."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.182"},{"key":"e_1_3_2_1_27_1","volume-title":"A method for stochastic optimization. arXiv preprint arXiv:1412.6980","author":"Kingma Diederik P","year":"2014","unstructured":"P Kingma Diederik and Jimmy Ba Adam. 2014. A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.19"},{"key":"e_1_3_2_1_29_1","volume-title":"Han Zhang, Dina Katabi, and Dilip Krishnan.","author":"Li Tianhong","year":"2022","unstructured":"Tianhong Li, Huiwen Chang, Shlok Kumar Mishra, Han Zhang, Dina Katabi, and Dilip Krishnan. 2022a. Mage: Masked generative encoder to unify representation learning and image synthesis. arXiv preprint arXiv:2211.09117 (2022)."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58545-7_23"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00278"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01261-8_17"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19800-7_22"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW54120.2021.00210"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.151"},{"key":"e_1_3_2_1_36_1","volume-title":"Reconstructed Convolution Module Based Look-Up Tables for Efficient Image Super-Resolution. arXiv preprint arXiv:2307.08544","author":"Liu Guandu","year":"2023","unstructured":"Guandu Liu, Yukang Ding, Mading Li, Ming Sun, Xing Wen, and Bin Wang. 2023. Reconstructed Convolution Module Based Look-Up Tables for Efficient Image Super-Resolution. arXiv preprint arXiv:2307.08544 (2023)."},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW56347.2022.00061"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2001.937655"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-016-4020-z"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00251"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19790-1_43"},{"key":"e_1_3_2_1_42_1","volume-title":"European conference on computer vision. Springer, 191--207","author":"Niu Ben","year":"2020","unstructured":"Ben Niu, Weilei Wen, Wenqi Ren, Xiangde Zhang, Lianping Yang, Shuzhen Wang, Kaihao Zhang, Xiaochun Cao, and Haifeng Shen. 2020. Single image super-resolution via a holistic attention network. In European conference on computer vision. Springer, 191--207."},{"key":"e_1_3_2_1_43_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_44_1","volume-title":"Chen Change Loy, and Ping Luo","author":"Pan Xingang","year":"2021","unstructured":"Xingang Pan, Xiaohang Zhan, Bo Dai, Dahua Lin, Chen Change Loy, and Ping Luo. 2021. Exploiting deep generative prior for versatile image restoration and manipulation. IEEE Transactions on Pattern Analysis and Machine Intelligence (2021)."},{"key":"e_1_3_2_1_45_1","volume-title":"Fully convolutional multi-class multiple instance learning. arXiv preprint arXiv:1412.7144","author":"Pathak Deepak","year":"2014","unstructured":"Deepak Pathak, Evan Shelhamer, Jonathan Long, and Trevor Darrell. 2014. Fully convolutional multi-class multiple instance learning. arXiv preprint arXiv:1412.7144 (2014)."},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D15-1303"},{"key":"e_1_3_2_1_47_1","volume-title":"Aaron Van den Oord, and Oriol Vinyals","author":"Razavi Ali","year":"2019","unstructured":"Ali Razavi, Aaron Van den Oord, and Oriol Vinyals. 2019a. Generating diverse high-fidelity images with vq-vae-2. Advances in neural information processing systems, Vol. 32 (2019)."},{"key":"e_1_3_2_1_48_1","unstructured":"Ali Razavi Aaron van den Oord and Oriol Vinyals. 2019b. Generating diverse high-resolution images with VQ-VAE. (2019)."},{"key":"e_1_3_2_1_49_1","volume-title":"Nonlinear dimensionality reduction by locally linear embedding. science","author":"Roweis Sam T","year":"2000","unstructured":"Sam T Roweis and Lawrence K Saul. 2000. Nonlinear dimensionality reduction by locally linear embedding. science, Vol. 290, 5500 (2000), 2323--2326."},{"key":"e_1_3_2_1_50_1","volume-title":"Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556","author":"Simonyan Karen","year":"2014","unstructured":"Karen Simonyan and Andrew Zisserman. 2014. Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556 (2014)."},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01097"},{"key":"e_1_3_2_1_52_1","unstructured":"Aaron Van Den Oord Oriol Vinyals et al. 2017. Neural discrete representation learning. Advances in neural information processing systems Vol. 30 (2017)."},{"key":"e_1_3_2_1_53_1","first-page":"2579","article-title":"Visualizing Data using t-SNE","volume":"9","author":"van der Maaten Laurens","year":"2008","unstructured":"Laurens van der Maaten and Geoffrey Hinton. 2008. Visualizing Data using t-SNE. Journal of Machine Learning Research, Vol. 9, 86 (2008), 2579--2605. http:\/\/jmlr.org\/papers\/v9\/vandermaaten08a.html","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00905"},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW54120.2021.00217"},{"key":"e_1_3_2_1_56_1","volume-title":"Proceedings of the European conference on computer vision (ECCV) workshops. 0-0.","author":"Wang Xintao","year":"2018","unstructured":"Xintao Wang, Ke Yu, Shixiang Wu, Jinjin Gu, Yihao Liu, Chao Dong, Yu Qiao, and Chen Change Loy. 2018. Esrgan: Enhanced super-resolution generative adversarial networks. In Proceedings of the European conference on computer vision (ECCV) workshops. 0-0."},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58598-3_7"},{"key":"e_1_3_2_1_58_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2023.3283922"},{"key":"e_1_3_2_1_59_1","volume-title":"IEEE Conference on Computer Vision and Pattern Recognition (CVPR).","author":"Xintao Wang Chao Dong","year":"2018","unstructured":"Chao Dong Xintao Wang, Ke Yu and Chen Change Loy. 2018. Recovering Realistic Texture in Image Super-resolution by Deep Spatial Feature Transform. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR)."},{"key":"e_1_3_2_1_60_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00583"},{"key":"e_1_3_2_1_61_1","volume-title":"Image super-resolution via sparse representation","author":"Yang Jianchao","year":"2010","unstructured":"Jianchao Yang, John Wright, Thomas S Huang, and Yi Ma. 2010. Image super-resolution via sparse representation. IEEE transactions on image processing, Vol. 19, 11 (2010), 2861--2873."},{"key":"e_1_3_2_1_62_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00073"},{"key":"e_1_3_2_1_63_1","volume-title":"Han Zhang, Ruoming Pang, James Qin, Alexander Ku, Yuanzhong Xu, Jason Baldridge, and Yonghui Wu.","author":"Yu Jiahui","year":"2021","unstructured":"Jiahui Yu, Xin Li, Jing Yu Koh, Han Zhang, Ruoming Pang, James Qin, Alexander Ku, Yuanzhong Xu, Jason Baldridge, and Yonghui Wu. 2021. Vector-quantized image modeling with improved vqgan. arXiv preprint arXiv:2110.04627 (2021)."},{"key":"e_1_3_2_1_64_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00217"},{"key":"e_1_3_2_1_65_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-27413-8_47"},{"key":"e_1_3_2_1_66_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00475"},{"key":"e_1_3_2_1_67_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00068"},{"key":"e_1_3_2_1_68_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01234-2_18"},{"key":"e_1_3_2_1_69_1","volume-title":"Residual non-local attention networks for image restoration. arXiv preprint arXiv:1903.10082","author":"Zhang Yulun","year":"2019","unstructured":"Yulun Zhang, Kunpeng Li, Kai Li, Bineng Zhong, and Yun Fu. 2019a. Residual non-local attention networks for image restoration. arXiv preprint arXiv:1903.10082 (2019)."},{"key":"e_1_3_2_1_70_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00262"},{"key":"e_1_3_2_1_71_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00817"},{"key":"e_1_3_2_1_72_1","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 22302--22313","author":"Zhao Kai","year":"2023","unstructured":"Kai Zhao, Kun Yuan, Ming Sun, Mading Li, and Xing Wen. 2023. Quality-aware pre-trained models for blind image quality assessment. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 22302--22313."},{"key":"e_1_3_2_1_73_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01231-1_6"},{"key":"e_1_3_2_1_74_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.544"},{"key":"e_1_3_2_1_75_1","first-page":"30599","article-title":"Towards robust blind face restoration with codebook lookup transformer","volume":"35","author":"Zhou Shangchen","year":"2022","unstructured":"Shangchen Zhou, Kelvin Chan, Chongyi Li, and Chen Change Loy. 2022. Towards robust blind face restoration with codebook lookup transformer. Advances in Neural Information Processing Systems, Vol. 35 (2022), 30599--30611.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_76_1","volume-title":"Cross-scale internal graph neural network for image super-resolution. Advances in neural information processing systems","author":"Zhou Shangchen","year":"2020","unstructured":"Shangchen Zhou, Jiawei Zhang, Wangmeng Zuo, and Chen Change Loy. 2020. Cross-scale internal graph neural network for image super-resolution. Advances in neural information processing systems, Vol. 33 (2020), 3499--3509."}],"event":{"name":"MM '23: The 31st ACM International Conference on Multimedia","location":"Ottawa ON Canada","acronym":"MM '23","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 31st ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3581783.3611917","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3581783.3611917","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:12:26Z","timestamp":1755821546000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3581783.3611917"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,26]]},"references-count":76,"alternative-id":["10.1145\/3581783.3611917","10.1145\/3581783"],"URL":"https:\/\/doi.org\/10.1145\/3581783.3611917","relation":{},"subject":[],"published":{"date-parts":[[2023,10,26]]},"assertion":[{"value":"2023-10-27","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}