{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,18]],"date-time":"2026-02-18T23:51:22Z","timestamp":1771458682477,"version":"3.50.1"},"publisher-location":"Cham","reference-count":62,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031197963","type":"print"},{"value":"9783031197970","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-19797-0_23","type":"book-chapter","created":{"date-parts":[[2022,11,2]],"date-time":"2022-11-02T20:28:41Z","timestamp":1667420921000},"page":"393-411","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Towards Interpretable Video Super-Resolution via\u00a0Alternating Optimization"],"prefix":"10.1007","author":[{"given":"Jiezhang","family":"Cao","sequence":"first","affiliation":[]},{"given":"Jingyun","family":"Liang","sequence":"additional","affiliation":[]},{"given":"Kai","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Wenguan","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Qin","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Yulun","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Hao","family":"Tang","sequence":"additional","affiliation":[]},{"given":"Luc","family":"Van Gool","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,11,3]]},"reference":[{"issue":"9","key":"23_CR1","doi-asserted-by":"publisher","first-page":"2345","DOI":"10.1109\/TIP.2010.2047910","volume":"19","author":"MV Afonso","year":"2010","unstructured":"Afonso, M.V., Bioucas-Dias, J.M., Figueiredo, M.A.: Fast image recovery using variable splitting and constrained optimization. IEEE Trans. Image Process. 19(9), 2345\u20132356 (2010)","journal-title":"IEEE Trans. Image Process."},{"key":"23_CR2","doi-asserted-by":"crossref","unstructured":"Argaw, D.M., Kim, J., Rameau, F., Kweon, I.S.: Motion-blurred video interpolation and extrapolation. In: AAAI Conference on Artificial Intelligence, pp. 901\u2013910 (2021)","DOI":"10.1609\/aaai.v35i2.16173"},{"key":"23_CR3","doi-asserted-by":"crossref","unstructured":"Bao, W., Lai, W.S., Ma, C., Zhang, X., Gao, Z., Yang, M.H.: Depth-aware video frame interpolation. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 3703\u20133712 (2019)","DOI":"10.1109\/CVPR.2019.00382"},{"issue":"3","key":"23_CR4","doi-asserted-by":"publisher","first-page":"933","DOI":"10.1109\/TPAMI.2019.2941941","volume":"43","author":"W Bao","year":"2019","unstructured":"Bao, W., Lai, W.S., Zhang, X., Gao, Z., Yang, M.H.: MEMC-Net: motion estimation and motion compensation driven neural network for video interpolation and enhancement. IEEE Trans. Pattern Anal. Mach. Intell. 43(3), 933\u2013948 (2019)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"23_CR5","doi-asserted-by":"crossref","unstructured":"Caballero, J., et al.: Real-time video super-resolution with spatio-temporal networks and motion compensation. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 4778\u20134787 (2017)","DOI":"10.1109\/CVPR.2017.304"},{"key":"23_CR6","doi-asserted-by":"crossref","unstructured":"Chan, K.C., Wang, X., Yu, K., Dong, C., Loy, C.C.: BasicVSR: the search for essential components in video super-resolution and beyond. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 4947\u20134956 (2021)","DOI":"10.1109\/CVPR46437.2021.00491"},{"key":"23_CR7","doi-asserted-by":"crossref","unstructured":"Chan, K.C., Zhou, S., Xu, X., Loy, C.C.: BasicVSR++: improving video super-resolution with enhanced propagation and alignment. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 5972\u20135981 (2022)","DOI":"10.1109\/CVPR52688.2022.00588"},{"key":"23_CR8","doi-asserted-by":"crossref","unstructured":"Charbonnier, P., Blanc-Feraud, L., Aubert, G., Barlaud, M.: Two deterministic half-quadratic regularization algorithms for computed imaging. In: International Conference on Image Processing, vol. 2, pp. 168\u2013172 (1994)","DOI":"10.1109\/ICIP.1994.413553"},{"key":"23_CR9","doi-asserted-by":"crossref","unstructured":"Chiche, B.N., Frontera-Pons, J., Woiselle, A., Starck, J.L.: Deep unrolled network for video super-resolution. In: International Conference on Image Processing Theory, Tools and Applications, pp. 1\u20136 (2020)","DOI":"10.1109\/IPTA50016.2020.9286636"},{"issue":"1","key":"23_CR10","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1109\/TSP.2014.2367457","volume":"63","author":"C Gilavert","year":"2014","unstructured":"Gilavert, C., Moussaoui, S., Idier, J.: Efficient Gaussian sampling for solving large-scale inverse problems using MCMC. IEEE Trans. Sig. Process. 63(1), 70\u201380 (2014)","journal-title":"IEEE Trans. Sig. Process."},{"key":"23_CR11","doi-asserted-by":"crossref","unstructured":"Gupta, A., Aich, A., Roy-Chowdhury, A.K.: ALANET: adaptive latent attention network forjoint video deblurring and interpolation. arXiv preprint arXiv:2009.01005 (2020)","DOI":"10.1145\/3394171.3413686"},{"key":"23_CR12","doi-asserted-by":"crossref","unstructured":"Haris, M., Shakhnarovich, G., Ukita, N.: Recurrent back-projection network for video super-resolution. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 3897\u20133906 (2019)","DOI":"10.1109\/CVPR.2019.00402"},{"key":"23_CR13","doi-asserted-by":"crossref","unstructured":"Hyun Kim, T., Mu Lee, K.: Generalized video deblurring for dynamic scenes. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 5426\u20135434 (2015)","DOI":"10.1109\/CVPR.2015.7299181"},{"key":"23_CR14","doi-asserted-by":"crossref","unstructured":"Hyun Kim, T., Mu Lee, K., Scholkopf, B., Hirsch, M.: Online video deblurring via dynamic temporal blending network. In: IEEE International Conference on Computer Vision, pp. 4038\u20134047 (2017)","DOI":"10.1109\/ICCV.2017.435"},{"key":"23_CR15","doi-asserted-by":"crossref","unstructured":"Jiang, H., Sun, D., Jampani, V., Yang, M.H., Learned-Miller, E., Kautz, J.: Super SloMo: high quality estimation of multiple intermediate frames for video interpolation. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 9000\u20139008 (2018)","DOI":"10.1109\/CVPR.2018.00938"},{"key":"23_CR16","doi-asserted-by":"crossref","unstructured":"Jin, M., Meishvili, G., Favaro, P.: Learning to extract a video sequence from a single motion-blurred image. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 6334\u20136342 (2018)","DOI":"10.1109\/CVPR.2018.00663"},{"key":"23_CR17","doi-asserted-by":"crossref","unstructured":"Jo, Y., Oh, S.W., Kang, J., Kim, S.J.: Deep video super-resolution network using dynamic upsampling filters without explicit motion compensation. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 3224\u20133232 (2018)","DOI":"10.1109\/CVPR.2018.00340"},{"issue":"10","key":"23_CR18","doi-asserted-by":"publisher","first-page":"2374","DOI":"10.1109\/TPAMI.2017.2761348","volume":"40","author":"TH Kim","year":"2017","unstructured":"Kim, T.H., Nah, S., Lee, K.M.: Dynamic video deblurring using a locally adaptive blur model. IEEE Trans. Pattern Anal. Mach. Intell. 40(10), 2374\u20132387 (2017)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"23_CR19","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. In: International Conference on Learning Representations (2015)"},{"key":"23_CR20","doi-asserted-by":"crossref","unstructured":"Kupyn, O., Budzan, V., Mykhailych, M., Mishkin, D., Matas, J.: DeblurGAN: blind motion deblurring using conditional adversarial networks. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 8183\u20138192 (2018)","DOI":"10.1109\/CVPR.2018.00854"},{"key":"23_CR21","unstructured":"Liang, J., et al.: VRT: a video restoration transformer. arXiv preprint arXiv:2201.12288 (2022)"},{"key":"23_CR22","doi-asserted-by":"crossref","unstructured":"Liang, J., Cao, J., Sun, G., Zhang, K., Van Gool, L., Timofte, R.: Swinir: image restoration using swin transformer. In: IEEE International Conference on Computer Vision Workshops, pp. 1833\u20131844 (2021)","DOI":"10.1109\/ICCVW54120.2021.00210"},{"key":"23_CR23","unstructured":"Liang, J., et al.: Recurrent video restoration transformer with guided deformable attention. arXiv preprint arXiv:2206.02146 (2022)"},{"key":"23_CR24","doi-asserted-by":"crossref","unstructured":"Liang, J., Sun, G., Zhang, K., Van Gool, L., Timofte, R.: Mutual affine network for spatially variant kernel estimation in blind image super-resolution. In: IEEE Conference on International Conference on Computer Vision, pp. 4096\u20134105 (2021)","DOI":"10.1109\/ICCV48922.2021.00406"},{"issue":"2","key":"23_CR25","doi-asserted-by":"publisher","first-page":"346","DOI":"10.1109\/TPAMI.2013.127","volume":"36","author":"C Liu","year":"2013","unstructured":"Liu, C., Sun, D.: On Bayesian adaptive video super resolution. IEEE Trans. Pattern Anal. Mach. Intell. 36(2), 346\u2013360 (2013)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"2","key":"23_CR26","doi-asserted-by":"publisher","first-page":"346","DOI":"10.1109\/TPAMI.2013.127","volume":"36","author":"C Liu","year":"2013","unstructured":"Liu, C., Sun, D.: On Bayesian adaptive video super resolution. IEEE Transactions on Pattern Anal. Mach. Intell. 36(2), 346\u2013360 (2013)","journal-title":"IEEE Transactions on Pattern Anal. Mach. Intell."},{"key":"23_CR27","doi-asserted-by":"crossref","unstructured":"Liu, Z., Yeh, R.A., Tang, X., Liu, Y., Agarwala, A.: Video frame synthesis using deep voxel flow. In: IEEE International Conference on Computer Vision, pp. 4463\u20134471 (2017)","DOI":"10.1109\/ICCV.2017.478"},{"key":"23_CR28","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"434","DOI":"10.1007\/978-3-319-46466-4_26","volume-title":"Computer Vision \u2013 ECCV 2016","author":"G Long","year":"2016","unstructured":"Long, G., Kneip, L., Alvarez, J.M., Li, H., Zhang, X., Yu, Q.: Learning image matching by simply watching video. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9910, pp. 434\u2013450. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46466-4_26"},{"key":"23_CR29","unstructured":"Loshchilov, I., Hutter, F.: SGDR: stochastic gradient descent with warm restarts. arXiv preprint arXiv:1608.03983 (2016)"},{"key":"23_CR30","doi-asserted-by":"crossref","unstructured":"Meyer, S., Wang, O., Zimmer, H., Grosse, M., Sorkine-Hornung, A.: Phase-based frame interpolation for video. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1410\u20131418 (2015)","DOI":"10.1109\/CVPR.2015.7298747"},{"issue":"5","key":"23_CR31","doi-asserted-by":"publisher","first-page":"995","DOI":"10.1109\/TPAMI.2010.167","volume":"33","author":"U Mudenagudi","year":"2010","unstructured":"Mudenagudi, U., Banerjee, S., Kalra, P.K.: Space-time super-resolution using graph-cut optimization. IEEE Trans. Pattern Anal. Mach. Intell. 33(5), 995\u20131008 (2010)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"23_CR32","doi-asserted-by":"crossref","unstructured":"Nah, S., et al.: NTIRE 2019 challenge on video deblurring and super-resolution: dataset and study. In: IEEE Conference on Computer Vision and Pattern Recognition Workshops (2019)","DOI":"10.1109\/CVPRW.2019.00251"},{"key":"23_CR33","doi-asserted-by":"crossref","unstructured":"Nah, S., Hyun Kim, T., Mu Lee, K.: Deep multi-scale convolutional neural network for dynamic scene deblurring. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 3883\u20133891 (2017)","DOI":"10.1109\/CVPR.2017.35"},{"key":"23_CR34","doi-asserted-by":"crossref","unstructured":"Nah, S., Son, S., Lee, K.M.: Recurrent neural networks with intra-frame iterations for video deblurring. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 8102\u20138111 (2019)","DOI":"10.1109\/CVPR.2019.00829"},{"key":"23_CR35","doi-asserted-by":"crossref","unstructured":"Niklaus, S., Liu, F.: Context-aware synthesis for video frame interpolation. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1701\u20131710 (2018)","DOI":"10.1109\/CVPR.2018.00183"},{"key":"23_CR36","doi-asserted-by":"crossref","unstructured":"Oh, J., Kim, M.: DeMFI: deep joint deblurring and multi-frame interpolation with flow-guided attentive correlation and recursive boosting. arXiv preprint arXiv:2111.09985 (2021)","DOI":"10.1007\/978-3-031-20071-7_12"},{"key":"23_CR37","doi-asserted-by":"crossref","unstructured":"Pan, J., Bai, H., Dong, J., Zhang, J., Tang, J.: Deep blind video super-resolution. In: IEEE International Conference on Computer Vision, pp. 4811\u20134820 (2021)","DOI":"10.1109\/ICCV48922.2021.00477"},{"key":"23_CR38","doi-asserted-by":"crossref","unstructured":"Pan, J., Bai, H., Tang, J.: Cascaded deep video deblurring using temporal sharpness prior. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 3043\u20133051 (2020)","DOI":"10.1109\/CVPR42600.2020.00311"},{"key":"23_CR39","doi-asserted-by":"crossref","unstructured":"Pollak Zuckerman, L., Naor, E., Pisha, G., Bagon, S., Irani, M.: Across scales & across dimensions: temporal super-resolution using deep internal learning. arXiv e-prints pp. arXiv-2003 (2020)","DOI":"10.1007\/978-3-030-58571-6_4"},{"issue":"10","key":"23_CR40","doi-asserted-by":"publisher","first-page":"2669","DOI":"10.1109\/TIP.2010.2050107","volume":"19","author":"MD Robinson","year":"2010","unstructured":"Robinson, M.D., Toth, C.A., Lo, J.Y., Farsiu, S.: Efficient Fourier-wavelet super-resolution. IEEE Trans. Image Process. 19(10), 2669\u20132681 (2010)","journal-title":"IEEE Trans. Image Process."},{"key":"23_CR41","doi-asserted-by":"crossref","unstructured":"Sajjadi, M.S., Vemulapalli, R., Brown, M.: Frame-recurrent video super-resolution. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 6626\u20136634 (2018)","DOI":"10.1109\/CVPR.2018.00693"},{"key":"23_CR42","doi-asserted-by":"crossref","unstructured":"Shahar, O., Faktor, A., Irani, M.: Space-time super-resolution from a single video. IEEE (2011)","DOI":"10.1109\/CVPR.2011.5995360"},{"key":"23_CR43","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"753","DOI":"10.1007\/3-540-47969-4_50","volume-title":"Computer Vision \u2014 ECCV 2002","author":"E Shechtman","year":"2002","unstructured":"Shechtman, E., Caspi, Y., Irani, M.: Increasing space-time resolution in video. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol. 2350, pp. 753\u2013768. Springer, Heidelberg (2002). https:\/\/doi.org\/10.1007\/3-540-47969-4_50"},{"key":"23_CR44","doi-asserted-by":"crossref","unstructured":"Shen, W., Bao, W., Zhai, G., Chen, L., Min, X., Gao, Z.: Blurry video frame interpolation. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 5114\u20135123 (2020)","DOI":"10.1109\/CVPR42600.2020.00516"},{"key":"23_CR45","doi-asserted-by":"crossref","unstructured":"\u0160roubek, F., Kamenick\u1ef3, J., Milanfar, P.: Superfast superresolution. In: IEEE International Conference on Image Processing, pp. 1153\u20131156 (2011)","DOI":"10.1109\/ICIP.2011.6115633"},{"key":"23_CR46","doi-asserted-by":"crossref","unstructured":"Su, S., Delbracio, M., Wang, J., Sapiro, G., Heidrich, W., Wang, O.: Deep video deblurring for hand-held cameras. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1279\u20131288 (2017)","DOI":"10.1109\/CVPR.2017.33"},{"key":"23_CR47","doi-asserted-by":"publisher","unstructured":"Takeda, H., Beek, P.v., Milanfar, P.: Spatiotemporal video upscaling using motion-assisted steering kernel (mask) regression. In: Mrak, M., Grgic, M., Kunt, M. (eds.) High-Quality Visual Experience. Signals and Communication Technology, pp. 245\u2013274. Springer (2010). https:\/\/doi.org\/10.1007\/978-3-642-12802-8_10","DOI":"10.1007\/978-3-642-12802-8_10"},{"key":"23_CR48","doi-asserted-by":"crossref","unstructured":"Tao, X., Gao, H., Liao, R., Wang, J., Jia, J.: Detail-revealing deep video super-resolution. In: IEEE International Conference on Computer Vision, pp. 4472\u20134480 (2017)","DOI":"10.1109\/ICCV.2017.479"},{"key":"23_CR49","doi-asserted-by":"crossref","unstructured":"Tao, X., Gao, H., Shen, X., Wang, J., Jia, J.: Scale-recurrent network for deep image deblurring. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 8174\u20138182 (2018)","DOI":"10.1109\/CVPR.2018.00853"},{"key":"23_CR50","doi-asserted-by":"crossref","unstructured":"Telleen, J., et al.: Synthetic shutter speed imaging. In: Computer Graphics Forum, vol. 26, pp. 591\u2013598 (2007)","DOI":"10.1111\/j.1467-8659.2007.01082.x"},{"key":"23_CR51","doi-asserted-by":"crossref","unstructured":"Tian, Y., Zhang, Y., Fu, Y., Xu, C.: TDAN: temporally-deformable alignment network for video super-resolution. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 3360\u20133369 (2020)","DOI":"10.1109\/CVPR42600.2020.00342"},{"key":"23_CR52","doi-asserted-by":"crossref","unstructured":"Wang, L., Guo, Y., Lin, Z., Deng, X., An, W.: Learning for video super-resolution through HR optical flow estimation. In: Asian Conference on Computer Vision, pp. 514\u2013529 (2018)","DOI":"10.1007\/978-3-030-20887-5_32"},{"key":"23_CR53","doi-asserted-by":"crossref","unstructured":"Wang, X., Chan, K.C., Yu, K., Dong, C., Change Loy, C.: EDVR: video restoration with enhanced deformable convolutional networks. In: IEEE Conference on Computer Vision and Pattern Recognition Workshops (2019)","DOI":"10.1109\/CVPRW.2019.00247"},{"issue":"4","key":"23_CR54","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600\u2013612 (2004)","journal-title":"IEEE Trans. Image Process."},{"key":"23_CR55","doi-asserted-by":"crossref","unstructured":"Xiang, X., Tian, Y., Zhang, Y., Fu, Y., Allebach, J.P., Xu, C.: Zooming slow-mo: fast and accurate one-stage space-time video super-resolution. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 3370\u20133379 (2020)","DOI":"10.1109\/CVPR42600.2020.00343"},{"key":"23_CR56","doi-asserted-by":"crossref","unstructured":"Xiao, Z., Xiong, Z., Fu, X., Liu, D., Zha, Z.J.: Space-time video super-resolution using temporal profiles. In: ACM International Conference on Multimedia, pp. 664\u2013672 (2020)","DOI":"10.1145\/3394171.3413667"},{"issue":"8","key":"23_CR57","doi-asserted-by":"publisher","first-page":"1106","DOI":"10.1007\/s11263-018-01144-2","volume":"127","author":"T Xue","year":"2019","unstructured":"Xue, T., Chen, B., Wu, J., Wei, D., Freeman, W.T.: Video enhancement with task-oriented flow. Int. J. Comput. Vis. 127(8), 1106\u20131125 (2019)","journal-title":"Int. J. Comput. Vis."},{"key":"23_CR58","doi-asserted-by":"crossref","unstructured":"Zamir, A.R., et al.: Feedback networks. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1308\u20131317 (2017)","DOI":"10.1109\/CVPR.2017.196"},{"key":"23_CR59","doi-asserted-by":"crossref","unstructured":"Zhang, K., Gool, L.V., Timofte, R.: Deep unfolding network for image super-resolution. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 3217\u20133226 (2020)","DOI":"10.1109\/CVPR42600.2020.00328"},{"issue":"1","key":"23_CR60","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.: Adversarial spatio-temporal learning for video deblurring. IEEE Trans. Image Process. 28(1), 291\u2013301 (2018)","journal-title":"IEEE Trans. Image Process."},{"issue":"8","key":"23_CR61","doi-asserted-by":"publisher","first-page":"3683","DOI":"10.1109\/TIP.2016.2567075","volume":"25","author":"N Zhao","year":"2016","unstructured":"Zhao, N., Wei, Q., Basarab, A., Dobigeon, N., Kouam\u00e9, D., Tourneret, J.Y.: Fast single image super-resolution using a new analytical solution for l2\u2013l2 problems. IEEE Trans. Image Process. 25(8), 3683\u20133697 (2016)","journal-title":"IEEE Trans. Image Process."},{"key":"23_CR62","doi-asserted-by":"crossref","unstructured":"Zhou, S., Zhang, J., Pan, J., Xie, H., Zuo, W., Ren, J.: Spatio-temporal filter adaptive network for video deblurring. In: IEEE International Conference on Computer Vision, pp. 2482\u20132491 (2019)","DOI":"10.1109\/ICCV.2019.00257"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2022"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-19797-0_23","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,7]],"date-time":"2024-10-07T03:40:02Z","timestamp":1728272402000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-19797-0_23"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031197963","9783031197970"],"references-count":62,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-19797-0_23","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"3 November 2022","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":"Tel Aviv","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Israel","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 October 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 October 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2022.ecva.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"5804","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"1645","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"28% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.21","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.91","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}