{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T01:01:29Z","timestamp":1776128489751,"version":"3.50.1"},"reference-count":64,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2020,3,4]],"date-time":"2020-03-04T00:00:00Z","timestamp":1583280000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,3,4]],"date-time":"2020-03-04T00:00:00Z","timestamp":1583280000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100000781","name":"European Research Council","doi-asserted-by":"publisher","award":["677195-IDIU"],"award-info":[{"award-number":["677195-IDIU"]}],"id":[{"id":"10.13039\/501100000781","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003443","name":"Ministry of Education and Science of the Russian Federation","doi-asserted-by":"crossref","award":["14.756.31.0001"],"award-info":[{"award-number":["14.756.31.0001"]}],"id":[{"id":"10.13039\/501100003443","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J Comput Vis"],"published-print":{"date-parts":[[2020,7]]},"DOI":"10.1007\/s11263-020-01303-4","type":"journal-article","created":{"date-parts":[[2020,3,4]],"date-time":"2020-03-04T15:02:32Z","timestamp":1583334152000},"page":"1867-1888","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":543,"title":["Deep Image Prior"],"prefix":"10.1007","volume":"128","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1020-9767","authenticated-orcid":false,"given":"Dmitry","family":"Ulyanov","sequence":"first","affiliation":[]},{"given":"Andrea","family":"Vedaldi","sequence":"additional","affiliation":[]},{"given":"Victor","family":"Lempitsky","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,3,4]]},"reference":[{"key":"1303_CR1","unstructured":"Athar, S., Burnaev, E., & Lempitsky, V. S. (2018). Latent convolutional models. In CoRR."},{"key":"1303_CR2","doi-asserted-by":"crossref","unstructured":"Bahat, Y., Efrat, N., & Irani, M. (2017). Non-uniform blind deblurring by reblurring. In Proceedings of CVPR (pp. 3286\u20133294). IEEE Computer Society.","DOI":"10.1109\/ICCV.2017.356"},{"key":"1303_CR3","doi-asserted-by":"crossref","unstructured":"Bevilacqua, M., Roumy, A., Guillemot, C., & Alberi-Morel, M. (2012) Low-complexity single-image super-resolution based on nonnegative neighbor embedding. In BMVC (pp. 1\u201310).","DOI":"10.5244\/C.26.135"},{"key":"1303_CR4","unstructured":"Bojanowski, P., Joulin, A., Lopez-Paz, D., & Szlam, A. (2017). Optimizing the latent space of generative networks. In CoRR."},{"key":"1303_CR5","unstructured":"Boominathan, L., Maniparambil, M., Gupta, H., Baburajan, R., & Mitra, K. (2018). Phase retrieval for fourier ptychography under varying amount of measurements. In CoRR."},{"key":"1303_CR6","doi-asserted-by":"crossref","unstructured":"Bristow, H., Eriksson, A. P., & Lucey, S. (2013). Fast convolutional sparse coding. In CVPR (pp. 391\u2013398). IEEE Computer Society.","DOI":"10.1109\/CVPR.2013.57"},{"key":"1303_CR7","unstructured":"Buades, A. (2005). NLM demo. Retrieved December 2017 from http:\/\/demo.ipol.im\/demo\/bcm_non_local_means_denoising\/."},{"key":"1303_CR8","doi-asserted-by":"crossref","unstructured":"Buades, A., Coll, B., & Morel, J. M. (2005). A non-local algorithm for image denoising. In Proceedings of CVPR (Vol.\u00a02, pp. 60\u201365). IEEE Computer Society.","DOI":"10.1109\/CVPR.2005.38"},{"key":"1303_CR9","doi-asserted-by":"crossref","unstructured":"Burger, M., Osher, S. J., Xu, J., & Gilboa, G. (2005). Nonlinear inverse scale space methods for image restoration. In Variational, geometric, and level set methods in computer vision, third international workshop, VLSM (pp. 25\u201336).","DOI":"10.1007\/11567646_3"},{"key":"1303_CR10","doi-asserted-by":"crossref","unstructured":"Burger, H. C., Schuler, C. J., & Harmeling, S. (2012). Image denoising: Can plain neural networks compete with bm3d? In CVPR (pp. 2392\u20132399).","DOI":"10.1109\/CVPR.2012.6247952"},{"issue":"8","key":"1303_CR11","doi-asserted-by":"publisher","first-page":"2080","DOI":"10.1109\/TIP.2007.901238","volume":"16","author":"K Dabov","year":"2007","unstructured":"Dabov, K., Foi, A., Katkovnik, V., & Egiazarian, K. (2007). Image denoising by sparse 3-D transform-domain collaborative filtering. IEEE Transactions on Image Processing, 16(8), 2080\u20132095.","journal-title":"IEEE Transactions on Image Processing"},{"key":"1303_CR12","doi-asserted-by":"crossref","unstructured":"Dong, C., Loy, C.C., He, K., & Tang, X. (2014). Learning a deep convolutional network for image super-resolution. In Proceedings of ECCV (pp. 184\u2013199).","DOI":"10.1007\/978-3-319-10593-2_13"},{"key":"1303_CR13","unstructured":"Dosovitskiy, A., & Brox, T. (2016a). Generating images with perceptual similarity metrics based on deep networks. In NIPS (pp. 658\u2013666)."},{"key":"1303_CR14","doi-asserted-by":"crossref","unstructured":"Dosovitskiy, A., & Brox, T. (2016b). Inverting convolutional networks with convolutional networks. In CVPR. IEEE Computer Society.","DOI":"10.1109\/CVPR.2016.522"},{"key":"1303_CR15","doi-asserted-by":"crossref","unstructured":"Dosovitskiy, A., Tobias\u00a0Springenberg, J., & Brox, T. (2015). Learning to generate chairs with convolutional neural networks. In Proceedings of CVPR (pp. 1538\u20131546).","DOI":"10.1109\/CVPR.2015.7298761"},{"key":"1303_CR16","unstructured":"Erhan, D., Bengio, Y., Courville, A., & Vincent, P. (2009). Visualizing higher-layer features of a deep network. Tech. Rep. Technical Report 1341, University of Montreal."},{"issue":"12","key":"1303_CR17","doi-asserted-by":"publisher","first-page":"2379","DOI":"10.1364\/JOSAA.4.002379","volume":"4","author":"DJ Field","year":"1987","unstructured":"Field, D. J. (1987). Relations between the statistics of natural images and the response properties of cortical cells. Josa A, 4(12), 2379\u20132394.","journal-title":"Josa A"},{"key":"1303_CR18","doi-asserted-by":"crossref","unstructured":"Glasner, D., Bagon, S., & Irani, M. (2009). Super-resolution from a single image. In Proceedings of ICCV (pp. 349\u2013356).","DOI":"10.1109\/ICCV.2009.5459271"},{"key":"1303_CR19","unstructured":"Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., & Bengio, Y. (2014). Generative adversarial nets. In Proceedings of NIPS (pp. 2672\u20132680)."},{"key":"1303_CR20","unstructured":"Grosse, R. B., Raina, R., Kwong, H., & Ng, A. Y. (2007). Shift-invariance sparse coding for audio classification. In UAI (pp. 149\u2013158). AUAI Press."},{"key":"1303_CR21","doi-asserted-by":"crossref","unstructured":"Gu, S., Zuo, W., Xie, Q., Meng, D., Feng, X., & Zhang, L. (2015). Convolutional sparse coding for image super-resolution. In ICCV (pp. 1823\u20131831). IEEE Computer Society.","DOI":"10.1109\/ICCV.2015.212"},{"issue":"6","key":"1303_CR22","doi-asserted-by":"publisher","first-page":"1397","DOI":"10.1109\/TPAMI.2012.213","volume":"35","author":"K He","year":"2013","unstructured":"He, K., Sun, J., & Tang, X. (2013). Guided image filtering. T-PAMI, 35(6), 1397\u20131409.","journal-title":"T-PAMI"},{"key":"1303_CR23","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., & Sun, J. (2015). Delving deep into rectifiers: Surpassing human-level performance on imagenet classification. In CVPR (pp. 1026\u20131034). IEEE Computer Society.","DOI":"10.1109\/ICCV.2015.123"},{"key":"1303_CR24","doi-asserted-by":"crossref","unstructured":"Heide, F., Heidrich, W., & Wetzstein, G. (2015). Fast and flexible convolutional sparse coding. In CVPR (pp. 5135\u20135143). IEEE Computer Society.","DOI":"10.1109\/CVPR.2015.7299149"},{"key":"1303_CR25","unstructured":"Huang, J., & Mumford, D. (1999). Statistics of natural images and models. In CVPR (pp. 1541\u20131547). IEEE Computer Society."},{"key":"1303_CR26","doi-asserted-by":"crossref","unstructured":"Huang, J.B., Singh, A., & Ahuja, N. (2015). Single image super-resolution from transformed self-exemplars. In CVPR (pp. 5197\u20135206). IEEE Computer Society.","DOI":"10.1109\/CVPR.2015.7299156"},{"key":"1303_CR27","doi-asserted-by":"crossref","unstructured":"Iizuka, S., Simo-Serra, E., & Ishikawa, H. (2017). Globally and locally consistent image completion. ACM Transactions on Graphics (Proceedings of SIGGRAPH)36(4), 107:1\u2013107:14 (2017)","DOI":"10.1145\/3072959.3073659"},{"key":"1303_CR28","unstructured":"Ilyas, A., Jalal, A., Asteri, E., Daskalakis, C., & Dimakis, A. G. (2017). The robust manifold defense: Adversarial training using generative models. In CoRR."},{"key":"1303_CR29","doi-asserted-by":"crossref","unstructured":"Kim, J., Lee, J. K., & Lee, K. M. (2016). Accurate image super-resolution using very deep convolutional networks. In CVPR (pp. 1646\u20131654). IEEE Computer Society.","DOI":"10.1109\/CVPR.2016.182"},{"key":"1303_CR30","unstructured":"Kingma, D. P., & Ba, J. (2014). Adam: A method for stochastic optimization. In CoRR."},{"key":"1303_CR31","unstructured":"Kingma, D. P., & Welling, M. (2014). Auto-encoding variational bayes. In Proceedings of ICLR."},{"key":"1303_CR32","unstructured":"Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2012). Imagenet classification with deep convolutional neural networks. In F.\u00a0Pereira, C. J. C. Burges, L.\u00a0Bottou, K. Q. Weinberger (Eds.) Advances in neural information processing systems (Vol. 25, pp. 1097\u20131105). New York:Curran Associates, Inc."},{"key":"1303_CR33","doi-asserted-by":"crossref","unstructured":"Lai, W. S., Huang, J. B., Ahuja, N., & Yang, M. H. (2017). Deep laplacian pyramid networks for fast and accurate super-resolution. In CVPR. IEEE Computer Society.","DOI":"10.1109\/CVPR.2017.618"},{"key":"1303_CR34","unstructured":"Lebrun, M. (2011). BM3D code. Retrieved December 2017 from https:\/\/github.com\/gfacciol\/bm3d."},{"key":"1303_CR35","doi-asserted-by":"crossref","unstructured":"Ledig, C., Theis, L., Huszar, F., Caballero, J., Cunningham, A., Acosta, A., et al. (2017). Photo-realistic single image super-resolution using a generative adversarial network. In CVPR. IEEE Computer Society.","DOI":"10.1109\/CVPR.2017.19"},{"key":"1303_CR36","unstructured":"Lefkimmiatis, S. (2016). Non-local color image denoising with convolutional neural networks. In CVPR. IEEE Computer Society."},{"key":"1303_CR37","doi-asserted-by":"crossref","unstructured":"Mahendran, A., & Vedaldi, A. (2015). Understanding deep image representations by inverting them. In CVPR. IEEE Computer Society.","DOI":"10.1109\/CVPR.2015.7299155"},{"key":"1303_CR38","doi-asserted-by":"crossref","unstructured":"Mahendran, A., & Vedaldi, A. (2016). Visualizing deep convolutional neural networks using natural pre-images. In IJCV.","DOI":"10.1007\/s11263-016-0911-8"},{"issue":"Jan","key":"1303_CR39","first-page":"19","volume":"11","author":"J Mairal","year":"2010","unstructured":"Mairal, J., Bach, F., Ponce, J., & Sapiro, G. (2010). Online learning for matrix factorization and sparse coding. Journal of Machine Learning Research, 11(Jan), 19\u201360.","journal-title":"Journal of Machine Learning Research"},{"issue":"7","key":"1303_CR40","doi-asserted-by":"publisher","first-page":"674","DOI":"10.1109\/34.192463","volume":"11","author":"SG Mallat","year":"1989","unstructured":"Mallat, S. G. (1989). A theory for multiresolution signal decomposition: The wavelet representation. PAMI, 11(7), 674\u2013693.","journal-title":"PAMI"},{"issue":"1","key":"1303_CR41","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1137\/080724289","volume":"2","author":"A Marquina","year":"2009","unstructured":"Marquina, A. (2009). Nonlinear inverse scale space methods for total variation blind deconvolution. SIAM Journal on Imaging Sciences, 2(1), 64\u201383.","journal-title":"SIAM Journal on Imaging Sciences"},{"issue":"83","key":"1303_CR42","first-page":"1","volume":"18","author":"V Papyan","year":"2017","unstructured":"Papyan, V., Romano, Y., & Elad, M. (2017). Convolutional neural networks analyzed via convolutional sparse coding. Journal of Machine Learning Research, 18(83), 1\u201352.","journal-title":"Journal of Machine Learning Research"},{"key":"1303_CR43","doi-asserted-by":"crossref","unstructured":"Papyan, V., Romano, Y., Sulam, J., & Elad, M. (2017). Convolutional dictionary learning via local processing. In ICCV. IEEE Computer Society.","DOI":"10.1109\/ICCV.2017.566"},{"issue":"3","key":"1303_CR44","doi-asserted-by":"publisher","first-page":"664","DOI":"10.1145\/1015706.1015777","volume":"23","author":"G Petschnigg","year":"2004","unstructured":"Petschnigg, G., Szeliski, R., Agrawala, M., Cohen, M. F., Hoppe, H., & Toyama, K. (2004). Digital photography with flash and no-flash image pairs. ACM Transactions on Graphics, 23(3), 664\u2013672.","journal-title":"ACM Transactions on Graphics"},{"key":"1303_CR45","doi-asserted-by":"crossref","unstructured":"Plotz, T., & Roth, S. (2017). Benchmarking denoising algorithms with real photographs. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 1586\u20131595).","DOI":"10.1109\/CVPR.2017.294"},{"key":"1303_CR46","unstructured":"Ren, J. S. J., Xu, L., Yan, Q., & Sun, W. (2015). Shepard convolutional neural networks. In NIPS (pp. 901\u2013909)."},{"issue":"2","key":"1303_CR47","first-page":"205","volume":"82","author":"S Roth","year":"2009","unstructured":"Roth, S., & Black, M. J. (2009). Fields of experts. CVPR, 82(2), 205\u2013229.","journal-title":"CVPR"},{"key":"1303_CR48","unstructured":"Ruderman, D. L., & Bialek, W. (1993). Statistics of natural images: Scaling in the woods. In NIPS (pp. 551\u2013558). Morgan Kaufmann."},{"key":"1303_CR49","unstructured":"Rudin, L. I., Osher, S., & Fatemi, E. (1992). Nonlinear total variation based noise removal algorithms. In Proceedings of the eleventh annual international conference of the center for nonlinear studies on experimental mathematics : Computational issues in nonlinear science: Computational issues in nonlinear science (pp. 259\u2013268). New York, NY, USA: Elsevier North-Holland, Inc."},{"key":"1303_CR50","doi-asserted-by":"crossref","unstructured":"Sajjadi, M. S. M., Scholkopf, B., & Hirsch, M. (2017). Enhancenet: Single image super-resolution through automated texture synthesis. In The IEEE international conference on computer vision (ICCV).","DOI":"10.1109\/ICCV.2017.481"},{"key":"1303_CR51","doi-asserted-by":"crossref","unstructured":"Scherzer, O., & Groetsch, C. W. (2001). Inverse scale space theory for inverse problems. In Scale-space and morphology in computer vision, third international conference (pp. 317\u2013325).","DOI":"10.1007\/3-540-47778-0_29"},{"key":"1303_CR52","unstructured":"Shedligeri, P. A., Shah, K., Kumar, D., & Mitra, K. (2018). Photorealistic image reconstruction from hybrid intensity and event based sensor. In CoRR."},{"key":"1303_CR53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00329","volume-title":"\u201cZero-shot\u201d super-resolution using deep internal learning","author":"A Shocher","year":"2018","unstructured":"Shocher, A., Cohen, N., & Irani, M. (2018). \u201cZero-shot\u201d super-resolution using deep internal learning. In CVPR: IEEE Computer Society."},{"key":"1303_CR54","doi-asserted-by":"crossref","unstructured":"Simoncelli, E. P., & Adelson, E. H. (1996). Noise removal via bayesian wavelet coring. In ICIP (1) (pp. 379\u2013382). IEEE Computer Society.","DOI":"10.1109\/ICIP.1996.559512"},{"key":"1303_CR55","unstructured":"Simonyan, K., & Zisserman, A. (2014). Very deep convolutional networks for large-scale image recognition. In CoRR."},{"key":"1303_CR56","doi-asserted-by":"crossref","unstructured":"Tai, Y., Yang, J., & Liu, X. (2017). Image super-resolution via deep recursive residual network. In CVPR. IEEE Computer Society.","DOI":"10.1109\/CVPR.2017.298"},{"key":"1303_CR57","unstructured":"Turiel, A., Mato, G., Parga, N., & Nadal, J. (1997). Self-similarity properties of natural images. In NIPS (pp. 836\u2013842). The MIT Press."},{"key":"1303_CR58","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1016\/B978-0-08-050753-8.50042-5","volume-title":"Graphics gems","author":"K Turkowski","year":"1990","unstructured":"Turkowski, K. (1990). Filters for common resampling-tasks. In A. S. Glassner (Ed.), Graphics gems (pp. 147\u2013165). Cambridge: Academic Press."},{"key":"1303_CR59","unstructured":"Ulyanov, D., Vedaldi, A., & Lempitsky, V. (2018). Deep image prior. In CVPR. IEEE Computer Society."},{"key":"1303_CR60","unstructured":"Veen, D. V., Jalal, A., Price, E., Vishwanath, S., & Dimakis, A. G. (2018). Compressed sensing with deep image prior and learned regularization. In CoRR."},{"key":"1303_CR61","doi-asserted-by":"crossref","unstructured":"Zeiler, M. D., Krishnan, D., Taylor, G. W., & Fergus, R. (2010). Deconvolutional networks. In Proceedings of CVPR (pp. 2528\u20132535). IEEE Computer Society.","DOI":"10.1109\/CVPR.2010.5539957"},{"key":"1303_CR62","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"711","DOI":"10.1007\/978-3-642-27413-8_47","volume-title":"Curves and Surfaces","author":"R Zeyde","year":"2010","unstructured":"Zeyde, R., Elad, M., & Protter, M. (2010). On single image scale-up using sparse-representations. In J. D. Boissonnat, A. Chenin, P. Cohen, C. Gout, T. Lyche, M.-L. Mazure, & L. L. Schumaker (Eds.), Curves and Surfaces (Vol. 6920, pp. 711\u2013730)., Lecture Notes in Computer Science Berlin: Springer."},{"key":"1303_CR63","unstructured":"Zhang, C., Bengio, S., Hardt, M., Recht, B., & Vinyals, O. (2017). Understanding deep learning requires rethinking generalization. In ICLR."},{"issue":"11","key":"1303_CR64","doi-asserted-by":"publisher","first-page":"1236","DOI":"10.1109\/34.632983","volume":"19","author":"SC Zhu","year":"1997","unstructured":"Zhu, S. C., & Mumford, D. (1997). Prior learning and gibbs reaction\u2013diffusion. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19(11), 1236\u20131250.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"}],"container-title":["International Journal of Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-020-01303-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11263-020-01303-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-020-01303-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,3,4]],"date-time":"2021-03-04T00:22:35Z","timestamp":1614817355000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11263-020-01303-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3,4]]},"references-count":64,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2020,7]]}},"alternative-id":["1303"],"URL":"https:\/\/doi.org\/10.1007\/s11263-020-01303-4","relation":{},"ISSN":["0920-5691","1573-1405"],"issn-type":[{"value":"0920-5691","type":"print"},{"value":"1573-1405","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,3,4]]},"assertion":[{"value":"6 September 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 February 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 March 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}