{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T16:07:10Z","timestamp":1775578030964,"version":"3.50.1"},"reference-count":61,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2023,12,11]],"date-time":"2023-12-11T00:00:00Z","timestamp":1702252800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,12,11]],"date-time":"2023-12-11T00:00:00Z","timestamp":1702252800000},"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":["Int J Comput Vis"],"published-print":{"date-parts":[[2024,5]]},"DOI":"10.1007\/s11263-023-01958-9","type":"journal-article","created":{"date-parts":[[2023,12,11]],"date-time":"2023-12-11T15:02:00Z","timestamp":1702306920000},"page":"1817-1834","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Fast Ultra High-Definition Video Deblurring via Multi-scale Separable Network"],"prefix":"10.1007","volume":"132","author":[{"given":"Wenqi","family":"Ren","sequence":"first","affiliation":[]},{"given":"Senyou","family":"Deng","sequence":"additional","affiliation":[]},{"given":"Kaihao","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Fenglong","family":"Song","sequence":"additional","affiliation":[]},{"given":"Xiaochun","family":"Cao","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4848-2304","authenticated-orcid":false,"given":"Ming-Hsuan","family":"Yang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,12,11]]},"reference":[{"key":"1958_CR1","doi-asserted-by":"crossref","unstructured":"Bar, L., Berkels, B., Rumpf, M., & Sapiro, G. (2007). A variational framework for simultaneous motion estimation and restoration of motion-blurred video. In IEEE international conference on computer vision.","DOI":"10.1109\/ICCV.2007.4409009"},{"key":"1958_CR2","doi-asserted-by":"crossref","unstructured":"Chen, L., Fang, F., Wang, T., & Zhang, G. (2019). Blind image deblurring with local maximum gradient prior. In IEEE conference on computer vision and pattern recognition.","DOI":"10.1109\/CVPR.2019.00184"},{"key":"1958_CR3","unstructured":"Chen, L. C., Papandreou, G., Schroff, F., & Adam, H. (2017). Rethinking atrous convolution for semantic image segmentation. arXiv preprint arXiv:1706.05587"},{"key":"1958_CR4","doi-asserted-by":"crossref","unstructured":"Cho, S., Matsushita, Y., & Lee, S. (2007). Removing non-uniform motion blur from images. In IEEE international conference on computer vision.","DOI":"10.1109\/ICCV.2007.4408904"},{"key":"1958_CR5","doi-asserted-by":"crossref","unstructured":"Deng, S., Ren, W., Yan, Y., Wang, T., Song, F., & Cao, X. (2021). Multi-scale separable network for ultra-high-definition video deblurring. In IEEE international conference on computer vision (pp. 14030\u201314039).","DOI":"10.1109\/ICCV48922.2021.01377"},{"issue":"7","key":"1958_CR6","doi-asserted-by":"publisher","first-page":"1838","DOI":"10.1109\/TIP.2011.2108306","volume":"20","author":"W Dong","year":"2011","unstructured":"Dong, W., Zhang, L., Shi, G., & Wu, X. (2011). Image deblurring and super-resolution by adaptive sparse domain selection and adaptive regularization. IEEE Transactions on Image Processing, 20(7), 1838\u20131857.","journal-title":"IEEE Transactions on Image Processing"},{"key":"1958_CR7","doi-asserted-by":"crossref","unstructured":"Gao, H., Tao, X., Shen, X., & Jia, J. (2019). Dynamic scene deblurring with parameter selective sharing and nested skip connections. In IEEE conference on computer vision and pattern recognition.","DOI":"10.1109\/CVPR.2019.00397"},{"key":"1958_CR8","doi-asserted-by":"crossref","unstructured":"Gong, D., Yang, J., Liu, L., Zhang, Y., Reid, I., Shen, C., Van Den\u00a0Hengel, A., & Shi, Q. (2017). From motion blur to motion flow: A deep learning solution for removing heterogeneous motion blur. In IEEE conference on computer vision and pattern recognition (pp. 2319\u20132328).","DOI":"10.1109\/CVPR.2017.405"},{"key":"1958_CR9","doi-asserted-by":"crossref","unstructured":"Hu, X., Ren, W., Yu, K., Zhang, K., Cao, X., Liu, W., & Menze, B. (2021). Pyramid architecture search for real-time image deblurring. In IEEE international conference on computer vision.","DOI":"10.1109\/ICCV48922.2021.00426"},{"issue":"3","key":"1958_CR10","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1007\/s11263-015-0821-1","volume":"115","author":"Z Hu","year":"2015","unstructured":"Hu, Z., & Yang, M. H. (2015). Learning good regions to deblur images. International Journal of Computer Vision, 115(3), 66.","journal-title":"International Journal of Computer Vision"},{"key":"1958_CR11","doi-asserted-by":"crossref","unstructured":"Hyun\u00a0Kim, T., Ahn, B., & Mu\u00a0Lee, K. (2013). Dynamic scene deblurring. In IEEE international conference on computer vision (pp. 3160\u20133167).","DOI":"10.1109\/ICCV.2013.392"},{"key":"1958_CR12","doi-asserted-by":"crossref","unstructured":"Hyun\u00a0Kim, T., & Mu\u00a0Lee, K. (2014). Segmentation-free dynamic scene deblurring. InIEEE conference on computer vision and pattern recognition (pp. 2766\u20132773).","DOI":"10.1109\/CVPR.2014.348"},{"key":"1958_CR13","doi-asserted-by":"crossref","unstructured":"Hyun\u00a0Kim, T., Mu\u00a0Lee, K., Scholkopf, B., & Hirsch, M. (2017). Online video deblurring via dynamic temporal blending network. In IEEE international conference on computer vision (pp. 4038\u20134047).","DOI":"10.1109\/ICCV.2017.435"},{"key":"1958_CR14","doi-asserted-by":"crossref","unstructured":"Janai, J., Guney, F., Wulff, J., Black, M. J., & Geiger, A. (2017). Slow flow: Exploiting high-speed cameras for accurate and diverse optical flow reference data. In IEEE conference on computer vision and pattern recognition.","DOI":"10.1109\/CVPR.2017.154"},{"key":"1958_CR15","unstructured":"Ji, H., & Wang, K. (2012). A two-stage approach to blind spatially-varying motion deblurring. In IEEE conference on computer vision and pattern recognition."},{"key":"1958_CR16","doi-asserted-by":"crossref","unstructured":"Jiang, Z., Zhang, Y., Zou, D., Ren, J., Lv, J., & Liu, Y. (2020). Learning event-based motion deblurring. In IEEE conference on computer vision and pattern recognition.","DOI":"10.1109\/CVPR42600.2020.00338"},{"key":"1958_CR17","unstructured":"Keskar, N. S., Mudigere, D., Nocedal, J., Smelyanskiy, M., & Tang, P. T. P. (2016). On large-batch training for deep learning: Generalization gap and sharp minima. In International conference on learning representations."},{"key":"1958_CR18","doi-asserted-by":"crossref","unstructured":"Kim, S. Y., Oh, J., & Kim, M. (2019). Deep sr-itm: Joint learning of super-resolution and inverse tone-mapping for 4k uhd hdr applications. In IEEE international conference on computer vision.","DOI":"10.1109\/ICCV.2019.00321"},{"key":"1958_CR19","unstructured":"Kingma, D. P., & Ba, J. (2014). Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980."},{"key":"1958_CR20","doi-asserted-by":"crossref","unstructured":"Krishnan, D., Tay, T., & Fergus, R. (2011). Blind deconvolution using a normalized sparsity measure. In IEEE conference on computer vision and pattern recognition.","DOI":"10.1109\/CVPR.2011.5995521"},{"key":"1958_CR21","doi-asserted-by":"crossref","unstructured":"Kupyn, O., Budzan, V., Mykhailych, M., Mishkin, D., & Matas, J. (2018). Deblurgan: Blind motion deblurring using conditional adversarial networks. In IEEE conference on computer vision and pattern recognition (pp. 8183\u20138192).","DOI":"10.1109\/CVPR.2018.00854"},{"key":"1958_CR22","doi-asserted-by":"crossref","unstructured":"Kupyn, O., Martyniuk, T., Wu, J., & Wang, Z. (2019). Deblurgan-v2: Deblurring (orders-of-magnitude) faster and better. In IEEE international conference on computer vision.","DOI":"10.1109\/ICCV.2019.00897"},{"key":"1958_CR23","unstructured":"Lai, W. S., Ding, J. J., Lin, Y. Y., & Chuang, Y. Y. (2015). Blur kernel estimation using normalized color-line prior. In IEEE conference on computer vision and pattern recognition."},{"key":"1958_CR24","doi-asserted-by":"crossref","unstructured":"Li, L., Pan, J., Lai, W.S., Gao, C., Sang, N., & Yang, M. H. (2018). Learning a discriminative prior for blind image deblurring. In IEEE conference on computer vision and pattern recognition.","DOI":"10.1109\/CVPR.2018.00692"},{"key":"1958_CR25","doi-asserted-by":"crossref","unstructured":"Liu, Z., Yeh, R. A., Tang, X., Liu, Y., & Agarwala, A. (2017). Video frame synthesis using deep voxel flow. In IEEE international conference on computer vision (pp. 4463\u20134471).","DOI":"10.1109\/ICCV.2017.478"},{"key":"1958_CR26","doi-asserted-by":"crossref","unstructured":"Michaeli, T., & Irani, M. (2014). Blind deblurring using internal patch recurrence. In European conference on computer vision.","DOI":"10.1007\/978-3-319-10578-9_51"},{"key":"1958_CR27","doi-asserted-by":"crossref","unstructured":"Nah, S., Baik, S., Hong, S., Moon, G., Son, S., Timofte, R., & Mu\u00a0Lee, K. (2019). Ntire 2019 challenge on video deblurring and super-resolution: Dataset and study. In IEEE conference on computer vision and pattern recognition workshops.","DOI":"10.1109\/CVPRW.2019.00251"},{"key":"1958_CR28","doi-asserted-by":"crossref","unstructured":"Nah, S., Hyun\u00a0Kim, T., & Mu\u00a0Lee, K. (2017). Deep multi-scale convolutional neural network for dynamic scene deblurring. In IEEE conference on computer vision and pattern recognition (pp. 3883\u20133891).","DOI":"10.1109\/CVPR.2017.35"},{"key":"1958_CR29","doi-asserted-by":"crossref","unstructured":"Nah, S., Son, S., & Lee, K. M. (2019). Recurrent neural networks with intra-frame iterations for video deblurring. In IEEE conference on computer vision and pattern recognition (pp. 8102\u20148111).","DOI":"10.1109\/CVPR.2019.00829"},{"key":"1958_CR30","doi-asserted-by":"crossref","unstructured":"Nah, S., Timofte, R., Baik, S., Hong, S., Moon, G., Son, S., & Mu\u00a0Lee, K. (2019). Ntire 2019 challenge on video deblurring: Methods and results. In IEEE conference on computer vision and pattern recognition workshops.","DOI":"10.1109\/CVPRW.2019.00249"},{"key":"1958_CR31","doi-asserted-by":"crossref","unstructured":"Nan, Y., Quan, Y., & Ji, H. (2020). Variational-em-based deep learning for noise-blind image deblurring. In IEEE conference on computer vision and pattern recognition.","DOI":"10.1109\/CVPR42600.2020.00368"},{"key":"1958_CR32","doi-asserted-by":"crossref","unstructured":"Niklaus, S., Mai, L., & Liu, F. (2017). Video frame interpolation via adaptive convolution. In IEEE conference on computer vision and pattern recognition (pp. 670\u2013679).","DOI":"10.1109\/CVPR.2017.244"},{"key":"1958_CR33","doi-asserted-by":"crossref","unstructured":"Pan, J., Bai, H., & Tang, J. (2020). Cascaded deep video deblurring using temporal sharpness prior. In IEEE conference on computer vision and pattern recognition (pp. 3043\u20133051).","DOI":"10.1109\/CVPR42600.2020.00311"},{"key":"1958_CR34","unstructured":"Parmar, N., Vaswani, A., Uszkoreit, J., Kaiser, \u0141., Shazeer, N., Ku, A., & Tran, D. (2018). Image transformer. arXiv preprint arXiv:1802.05751"},{"key":"1958_CR35","doi-asserted-by":"crossref","unstructured":"Perrone, D., & Favaro, P. (2014). Total variation blind deconvolution: The devil is in the details. In IEEE conference on computer vision and pattern recognition.","DOI":"10.1109\/CVPR.2014.372"},{"key":"1958_CR36","doi-asserted-by":"crossref","unstructured":"Ren, W., Pan, J., Cao, X., & Yang, M. H. (2017). Video deblurring via semantic segmentation and pixel-wise non-linear kernel. In IEEE international conference on computer vision (pp. 1077\u20131085).","DOI":"10.1109\/ICCV.2017.123"},{"issue":"7","key":"1958_CR37","doi-asserted-by":"publisher","first-page":"1439","DOI":"10.1109\/TPAMI.2015.2481418","volume":"38","author":"CJ Schuler","year":"2015","unstructured":"Schuler, C. J., Hirsch, M., Harmeling, S., & Sch\u00f6lkopf, B. (2015). Learning to deblur. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(7), 1439\u20131451.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"3","key":"1958_CR38","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1360612.1360672","volume":"27","author":"Q Shan","year":"2008","unstructured":"Shan, Q., Jia, J., & Agarwala, A. (2008). High-quality motion deblurring from a single image. ACM Transactions on Graphics, 27(3), 1\u201310.","journal-title":"ACM Transactions on Graphics"},{"key":"1958_CR39","doi-asserted-by":"crossref","unstructured":"Su, S., Delbracio, M., Wang, J., Sapiro, G., Heidrich, W., & Wang, O. (2017). Deep video deblurring for hand-held cameras. In IEEE conference on computer vision and pattern recognition (pp. 1279\u20131288).","DOI":"10.1109\/CVPR.2017.33"},{"key":"1958_CR40","doi-asserted-by":"crossref","unstructured":"Suin, M., Purohit, K., & Rajagopalan, A. (2020). Spatially-attentive patch-hierarchical network for adaptive motion deblurring. In IEEE conference on computer vision and pattern recognition (pp. 3606\u20133615).","DOI":"10.1109\/CVPR42600.2020.00366"},{"key":"1958_CR41","doi-asserted-by":"crossref","unstructured":"Sun, J., Cao, W., Xu, Z., & Ponce, J. (2015). Learning a convolutional neural network for non-uniform motion blur removal. In IEEE conference on computer vision and pattern recognition (pp. 769\u2013777).","DOI":"10.1109\/CVPR.2015.7298677"},{"key":"1958_CR42","unstructured":"Sun, L., Cho, S., Wang, J., & Hays, J. (2013). Edge-based blur kernel estimation using patch priors. In IEEE international conference on computational photography."},{"key":"1958_CR43","doi-asserted-by":"crossref","unstructured":"Tao, X., Gao, H., Liao, R., Wang, J., & Jia, J. (2017). Detail-revealing deep video super-resolution. In IEEE international conference on computer vision (pp. 4472\u20134480).","DOI":"10.1109\/ICCV.2017.479"},{"key":"1958_CR44","doi-asserted-by":"crossref","unstructured":"Tao, X., Gao, H., Shen, X., Wang, J., & Jia, J. (2018). Scale-recurrent network for deep image deblurring. In IEEE conference on computer vision and pattern recognition (pp. 8174\u20138182).","DOI":"10.1109\/CVPR.2018.00853"},{"key":"1958_CR45","doi-asserted-by":"crossref","unstructured":"Wang, P., Chen, P., Yuan, Y., Liu, D., Huang, Z., Hou, X., & Cottrell, G. (2018). Understanding convolution for semantic segmentation. In IEEE winter conference on applications of computer vision (pp. 1451\u20131460).","DOI":"10.1109\/WACV.2018.00163"},{"key":"1958_CR46","doi-asserted-by":"crossref","unstructured":"Wang, X., Chan, K. C., Yu, K., Dong, C., & Change\u00a0Loy, C. (2019). Edvr: Video restoration with enhanced deformable convolutional networks. In IEEE conference on computer vision and pattern recognition workshops.","DOI":"10.1109\/CVPRW.2019.00247"},{"key":"1958_CR47","doi-asserted-by":"crossref","unstructured":"Wieschollek, P., Hirsch, M., Scholkopf, B., & Lensch, H. P. A. (2017). Learning blind motion deblurring. In IEEE international conference on computer vision.","DOI":"10.1109\/ICCV.2017.34"},{"key":"1958_CR48","doi-asserted-by":"crossref","unstructured":"Wulff, J., & Black, M. J. (2014). Modeling blurred video with layers. In European conference on computer vision (pp. 236\u2013252).","DOI":"10.1007\/978-3-319-10599-4_16"},{"key":"1958_CR49","doi-asserted-by":"crossref","unstructured":"Xu, L., Zheng, S., & Jia, J. (2013). Unnatural l0 sparse representation for natural image deblurring. In IEEE conference on computer vision and pattern recognition.","DOI":"10.1109\/CVPR.2013.147"},{"key":"1958_CR50","unstructured":"Yu, F., & Koltun, V. (2015). Multi-scale context aggregation by dilated convolutions. arXiv preprint arXiv:1511.07122"},{"key":"1958_CR51","doi-asserted-by":"crossref","unstructured":"Zamir, S. W., Arora, A., Khan, S., Hayat, M., Khan, F. S., Yang, M. H., & Shao, L. (2021). Multi-stage progressive image restoration. arXiv preprint arXiv:2102.02808","DOI":"10.1109\/CVPR46437.2021.01458"},{"key":"1958_CR52","first-page":"66","volume":"6","author":"H Zeng","year":"2020","unstructured":"Zeng, H., Cai, J., Li, L., Cao, Z., & Zhang, L. (2020). Learning image-adaptive 3d lookup tables for high performance photo enhancement in real-time. IEEE Transactions on Pattern Analysis and Machine Intelligence, 6, 66.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"1958_CR53","doi-asserted-by":"crossref","unstructured":"Zhang, H., Dai, Y., Li, H., & Koniusz, P. (2019). Deep stacked hierarchical multi-patch network for image deblurring. In IEEE conference on computer vision and pattern recognition (pp. 5978\u20135986).","DOI":"10.1109\/CVPR.2019.00613"},{"key":"1958_CR54","doi-asserted-by":"crossref","unstructured":"Zhang, J., Pan, J., Ren, J., Song, Y., Bao, L., Lau, R. W., & Yang, M. H. (2018). Dynamic scene deblurring using spatially variant recurrent neural networks. In IEEE conference on computer vision and pattern recognition.","DOI":"10.1109\/CVPR.2018.00267"},{"issue":"1","key":"1958_CR55","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1109\/TIP.2018.2867733","volume":"28","author":"K Zhang","year":"2018","unstructured":"Zhang, K., Luo, W., Zhong, Y., Ma, L., Liu, W., & Li, H. (2018). Adversarial spatio-temporal learning for video deblurring. IEEE Transactions on Image Processing, 28(1), 291\u2013301.","journal-title":"IEEE Transactions on Image Processing"},{"key":"1958_CR56","doi-asserted-by":"crossref","unstructured":"Zhang, K., Luo, W., Zhong, Y., Ma, L., Stenger, B., Liu, W., & Li, H. (2020). Deblurring by realistic blurring. In IEEE conference on computer vision and pattern recognition (pp. 2737\u20132746).","DOI":"10.1109\/CVPR42600.2020.00281"},{"key":"1958_CR57","doi-asserted-by":"crossref","unstructured":"Zhang, K., Zuo, W., & Zhang, L. (2019). Deep plug-and-play super-resolution for arbitrary blur kernels. In IEEE conference on computer vision and pattern recognition.","DOI":"10.1109\/CVPR.2019.00177"},{"key":"1958_CR58","doi-asserted-by":"crossref","unstructured":"Zhao, Z., Xiong, B., Gai, S., & Wang, L. (2020). Improved deep multi-patch hierarchical network with nested module for dynamic scene deblurring. IEEE Access, 8, 62116\u201362126.","DOI":"10.1109\/ACCESS.2020.2984002"},{"key":"1958_CR59","doi-asserted-by":"crossref","unstructured":"Zhong, Z., Gao, Y., Zheng, Y., & Zheng, B. (2020). Efficient spatio-temporal recurrent neural network for video deblurring. In European conference on computer vision (pp. 191\u2013207). Springer.","DOI":"10.1007\/978-3-030-58539-6_12"},{"key":"1958_CR60","doi-asserted-by":"crossref","unstructured":"Zhou, S., Zhang, J., Pan, J., Xie, H., Zuo, W., & Ren, J. (2019). Spatio-temporal filter adaptive network for video deblurring. In IEEE international conference on computer vision (pp. 2482\u20132491).","DOI":"10.1109\/ICCV.2019.00257"},{"key":"1958_CR61","doi-asserted-by":"crossref","unstructured":"Zhou, Y., & Komodakis, N. (2014). A map-estimation framework for blind deblurring using high-level edge priors. In European conference on computer vision.","DOI":"10.1007\/978-3-319-10605-2_10"}],"container-title":["International Journal of Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-023-01958-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11263-023-01958-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-023-01958-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,7]],"date-time":"2024-05-07T08:18:35Z","timestamp":1715069915000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11263-023-01958-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,11]]},"references-count":61,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2024,5]]}},"alternative-id":["1958"],"URL":"https:\/\/doi.org\/10.1007\/s11263-023-01958-9","relation":{},"ISSN":["0920-5691","1573-1405"],"issn-type":[{"value":"0920-5691","type":"print"},{"value":"1573-1405","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12,11]]},"assertion":[{"value":"19 December 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 November 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 December 2023","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}