{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T03:23:14Z","timestamp":1774495394965,"version":"3.50.1"},"reference-count":37,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2021,3,4]],"date-time":"2021-03-04T00:00:00Z","timestamp":1614816000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,3,4]],"date-time":"2021-03-04T00:00:00Z","timestamp":1614816000000},"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":["Int J Comput Vis"],"published-print":{"date-parts":[[2021,5]]},"DOI":"10.1007\/s11263-021-01431-5","type":"journal-article","created":{"date-parts":[[2021,3,4]],"date-time":"2021-03-04T07:02:56Z","timestamp":1614841376000},"page":"1754-1767","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":240,"title":["You Only Look Yourself: Unsupervised and Untrained Single Image Dehazing Neural Network"],"prefix":"10.1007","volume":"129","author":[{"given":"Boyun","family":"Li","sequence":"first","affiliation":[]},{"given":"Yuanbiao","family":"Gou","sequence":"additional","affiliation":[]},{"given":"Shuhang","family":"Gu","sequence":"additional","affiliation":[]},{"given":"Jerry Zitao","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Joey Tianyi","family":"Zhou","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5727-2790","authenticated-orcid":false,"given":"Xi","family":"Peng","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,3,4]]},"reference":[{"key":"1431_CR1","unstructured":"Ancuti, C., Ancuti, C. O., Timofte, R., Van Gool, L., Zhang, L., & Yang, M., et al. (2018a). NTIRE 2018 challenge on image dehazing: Methods and results. In IEEE conference on computer vision and pattern recognition workshops (pp. 1004\u20131014). Salt Lake City, UT."},{"key":"1431_CR2","doi-asserted-by":"crossref","unstructured":"Ancuti, C., Ancuti, C. O., Timofte, R., & De Vleeschouwer, C. (2018b). I-HAZE: A dehazing benchmark with real hazy and haze-free indoor images. In Advanced concepts for intelligent vision systems (pp. 620\u2013631). Poitiers, France.","DOI":"10.1007\/978-3-030-01449-0_52"},{"key":"1431_CR3","doi-asserted-by":"crossref","unstructured":"Ancuti, C. O., Ancuti, C., Timofte, R., & De Vleeschouwer, C. (2018c). O-HAZE: A dehazing benchmark with real hazy and haze-free outdoor images. In IEEE conference on computer vision and pattern recognition workShops (pp. 754\u2013762). Salt Lake City, UT.","DOI":"10.1109\/CVPRW.2018.00119"},{"key":"1431_CR4","doi-asserted-by":"crossref","unstructured":"Berman, D., Treibitz, T., & Avidan, S. (2016). Non-local image dehazing. In IEEE conference on computer vision and pattern recognition (pp. 1674\u20131682). NV: Las Vegas.","DOI":"10.1109\/CVPR.2016.185"},{"key":"1431_CR5","doi-asserted-by":"crossref","unstructured":"Berman, D., Treibitz, T., & Avidan, S. (2017). Air-light estimation using haze-lines. In IEEE international conference on computational photography (pp. 1\u20139). Romania: Cluj-Napoca.","DOI":"10.1109\/ICCPHOT.2017.7951489"},{"issue":"11","key":"1431_CR6","doi-asserted-by":"publisher","first-page":"5187","DOI":"10.1109\/TIP.2016.2598681","volume":"25","author":"B Cai","year":"2016","unstructured":"Cai, B., Xu, X., Jia, K., Qing, C., & Tao, D. (2016). DehazeNet: An end-to-end system for single image haze removal. IEEE Transactions on Image Processing, 25(11), 5187\u20135198.","journal-title":"IEEE Transactions on Image Processing"},{"key":"1431_CR7","doi-asserted-by":"crossref","unstructured":"Chen, C., Do, M. N., & Wang, J. (2016). Robust image and video dehazing with visual artifact suppression via gradient residual minimization. In European conference on computer vision (pp. 576\u2013591). Amsterdam, The Netherlands.","DOI":"10.1007\/978-3-319-46475-6_36"},{"key":"1431_CR8","unstructured":"Gou, Y., Li, B., Liu, Z., Yang, S., Peng, X. (2020). CLEARER: Multi-Scale neural architecture search for image restoration. In Neural information processing systems. Canada: Vancouver."},{"key":"1431_CR9","doi-asserted-by":"crossref","unstructured":"Hahner, M., Sakaridis, D D., Zaech, C. & Gool L. V. J. (2019). Semantic understanding of foggy scenes with purely synthetic data. In IEEE intelligent transportation systems conference, New Zealand (pp. 3675\u20133681).","DOI":"10.1109\/ITSC.2019.8917518"},{"key":"1431_CR10","unstructured":"He, K., Sun, J., & Tang, X. (2009). Single image haze removal using dark channel prior. In IEEE conference on computer vision and pattern recognition (pp. 1956\u20131963). Miami, Florida, USA."},{"key":"1431_CR11","unstructured":"Heckel, R., & Hand, P. (2019) Deep decoder: Concise image representations from untrained non-convolutional networks. In International conference on learning representations, New Orleans, LA."},{"key":"1431_CR12","unstructured":"Ioffe, S., & Szegedy, C. (2015). Batch normalization: Accelerating deep network training by reducing internal covariate shift. In International conference on machine learning (pp. 448\u2013456). Lille, France."},{"key":"1431_CR13","unstructured":"Irani, M. (2019). Double-DIP: Unsupervised image decomposition via coupled deep-image-priors. In IEEE conference on computer vision and pattern recognition (pp. 11026\u201311035). Long Beach, CA."},{"key":"1431_CR14","unstructured":"Kingma, D. P., & Welling, M. (2014). Auto-encoding variational bayes. In International conference on learning representations, Banff, Canada."},{"key":"1431_CR15","unstructured":"Kingma, J., & Diederikand, B. (2015). Adam: A method for stochastic optimization. In International conference on learning representations, San Diego, CA."},{"key":"1431_CR16","doi-asserted-by":"crossref","unstructured":"Krull, A., Buchholz, T. O., & Jug, F. (2019). Noise2Void\u2014Learning denoising from single noisy images. In IEEE conference on computer vision and pattern recognition (pp. 2129\u20132137). Long Beach, CA.","DOI":"10.1109\/CVPR.2019.00223"},{"key":"1431_CR17","unstructured":"Lehtinen, J., Munkberg, J., Hasselgren, J., Laine, S., Karras, T., Aittala, M., et al. (2018). Noise2Noise: Learning image restoration without clean data. In International conference on machine learning (pp. 2971\u20132980). Stockholm, Sweden."},{"key":"1431_CR18","doi-asserted-by":"crossref","unstructured":"Li, B., Peng, X., Wang, Z., Xu, J., & Feng, D. (2017). AOD-net: All-in-one dehazing network. In International conference on computer vision (pp. 4780\u20134788). Venice, Italy.","DOI":"10.1109\/ICCV.2017.511"},{"issue":"1","key":"1431_CR19","doi-asserted-by":"publisher","first-page":"492","DOI":"10.1109\/TIP.2018.2867951","volume":"28","author":"B Li","year":"2019","unstructured":"Li, B., Ren, W., Fu, D., Tao, D., Feng, D., Zeng, W., et al. (2019). Benchmarking single image dehazing and beyond. IEEE Transactions on Image Processing, 28(1), 492\u2013505.","journal-title":"IEEE Transactions on Image Processing"},{"key":"1431_CR20","doi-asserted-by":"crossref","unstructured":"Li, R., Pan, J., Li, Z., & Tang, J. (2018). Single image dehazing via conditional generative adversarial network. In IEEE conference on computer vision and pattern recognition (pp. 8202\u20138211). Salt Lake City, UT.","DOI":"10.1109\/CVPR.2018.00856"},{"key":"1431_CR21","doi-asserted-by":"crossref","unstructured":"Li, Y., Tan, R. T., & Brown, M. S. (2015). Nighttime haze removal with glow and multiple light colors. In The IEEE international conference on computer vision (ICCV) (pp. 226\u2013234). Santiago, Chile.","DOI":"10.1109\/ICCV.2015.34"},{"key":"1431_CR22","doi-asserted-by":"crossref","unstructured":"Liu, X., Ma, Y., Shi, Z., & Chen, J. (2019). GridDehazeNet: Attention-based multi-scale network for image dehazing. In International conference on computer vision (pp. 7314\u20137323). Seoul, Korea.","DOI":"10.1109\/ICCV.2019.00741"},{"key":"1431_CR23","doi-asserted-by":"crossref","unstructured":"Mei, K., Jiang, A., Li, J., & Wang, M. (2018). Progressive feature fusion network for realistic image dehazing. In Asian conference on computer vision (ACCV) (pp. 203\u2013215). Perth, Australia","DOI":"10.1007\/978-3-030-20887-5_13"},{"key":"1431_CR24","doi-asserted-by":"crossref","unstructured":"Meng, G., Wang, Y., Duan, J., Xiang, S., & Pan, C. (2013). Efficient image dehazing with boundary constraint and contextual regularization. In International conference on computer vision (pp. 617\u2013624). Sydney, Australia.","DOI":"10.1109\/ICCV.2013.82"},{"key":"1431_CR25","doi-asserted-by":"crossref","unstructured":"Nayar, S. K., & Narasimhan, S. G. (1999). Vision in bad weather. In IEEE international conference on computer vision, Kerkyra, Corfu, Greece (Vol. 2, pp. 820\u2013827).","DOI":"10.1109\/ICCV.1999.790306"},{"key":"1431_CR26","doi-asserted-by":"crossref","unstructured":"Qu, Y., Chen, Y., Huang, J., & Xie, Y. (2019). Enhanced Pix2pix dehazing network. In IEEE conference on computer vision and pattern recognition (pp. 8160\u20138168). Long Beach, CA.","DOI":"10.1109\/CVPR.2019.00835"},{"key":"1431_CR27","doi-asserted-by":"crossref","unstructured":"Ren, W., Liu, S., Zhang, H., Pan, J., Cao, X., & Yang, M. H. (2016). Single image dehazing via multi-scale convolutional neural networks. In European conference on computer vision (pp. 154\u2013169). Amsterdam, The Netherlands.","DOI":"10.1007\/978-3-319-46475-6_10"},{"key":"1431_CR28","doi-asserted-by":"crossref","unstructured":"Sakaridis, C., Dai, D., Hecker, S., & Van Gool, L. (2018a). Model adaptation with synthetic and real data for semantic dense foggy scene understanding. In The European conference on computer vision, Munich, Germany (Vol. 11217, pp. 707\u2013724).","DOI":"10.1007\/978-3-030-01261-8_42"},{"key":"1431_CR29","doi-asserted-by":"crossref","unstructured":"Sakaridis, C., Dai, D., & Van Gool, L. (2018b). Semantic foggy scene understanding with synthetic data. International Journal of Computer Vision, 126, 973\u2013992.","DOI":"10.1007\/s11263-018-1072-8"},{"key":"1431_CR30","doi-asserted-by":"crossref","unstructured":"Tan, R. T. (2008). Visibility in bad weather from a single image. In IEEE conference on computer vision and pattern recognition","DOI":"10.1109\/CVPR.2008.4587643"},{"key":"1431_CR31","doi-asserted-by":"crossref","unstructured":"Tarel, J. P., & Hautiere, N. (2009). Fast visibility restoration from a single color or gray level image. In International conference on computer vision (pp. 2201\u20132208). Kyoto, Japan.","DOI":"10.1109\/ICCV.2009.5459251"},{"key":"1431_CR32","unstructured":"Ulyanov, D., Vedaldi, A., & Lempitsky, V. (2018). Deep image prior. In IEEE conference on computer vision and pattern recognition (pp. 9446\u20139454). Salt Lake City, UT."},{"key":"1431_CR33","doi-asserted-by":"crossref","unstructured":"Zhang, H., & Patel, V. M. (2018). Densely connected pyramid dehazing network. In IEEE conference on computer vision and pattern recognition (pp. 3194\u20133203). Salt Lake City, UT.","DOI":"10.1109\/CVPR.2018.00337"},{"key":"1431_CR34","unstructured":"Zhang, H., Sindagi, V., Patel, V. M. (2017). Joint transmission map estimation and dehazing using deep networks. CoRR arXiv:1708.00581"},{"key":"1431_CR35","doi-asserted-by":"crossref","unstructured":"Zhang, H., Sindagi, V., Patel, V. M. (2018). Multi-scale single image dehazing using perceptual pyramid deep network. In The IEEE conference on computer vision and pattern recognition workshops","DOI":"10.1109\/CVPRW.2018.00135"},{"key":"1431_CR36","doi-asserted-by":"crossref","unstructured":"Zhu, H., Peng, X., Chandrasekhar, V., Li, L., & Lim, J-H. (2018). DehazeGAN: When image dehazing meets differential programming. In International joint conferences on artificial intelligence (pp. 1234\u20131240). Stockholm, Sweden.","DOI":"10.24963\/ijcai.2018\/172"},{"key":"1431_CR37","doi-asserted-by":"publisher","first-page":"3522","DOI":"10.1109\/TIP.2015.2446191","volume":"24","author":"Q Zhu","year":"2015","unstructured":"Zhu, Q., Mai, J., & Shao, L. (2015). A fast single image haze removal algorithm using color attenuation prior. IEEE Transactions on Image Processing, 24, 3522\u20133533.","journal-title":"IEEE Transactions on Image Processing"}],"container-title":["International Journal of Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-021-01431-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11263-021-01431-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11263-021-01431-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,5,5]],"date-time":"2021-05-05T17:25:12Z","timestamp":1620235512000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11263-021-01431-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,3,4]]},"references-count":37,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2021,5]]}},"alternative-id":["1431"],"URL":"https:\/\/doi.org\/10.1007\/s11263-021-01431-5","relation":{},"ISSN":["0920-5691","1573-1405"],"issn-type":[{"value":"0920-5691","type":"print"},{"value":"1573-1405","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,3,4]]},"assertion":[{"value":"12 February 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 January 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 March 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}