{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T20:27:37Z","timestamp":1776889657232,"version":"3.51.2"},"publisher-location":"Cham","reference-count":44,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031726576","type":"print"},{"value":"9783031726583","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,10,2]],"date-time":"2024-10-02T00:00:00Z","timestamp":1727827200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,10,2]],"date-time":"2024-10-02T00:00:00Z","timestamp":1727827200000},"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":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-72658-3_15","type":"book-chapter","created":{"date-parts":[[2024,10,2]],"date-time":"2024-10-02T03:32:37Z","timestamp":1727839957000},"page":"252-268","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Unsupervised Exposure Correction"],"prefix":"10.1007","author":[{"given":"Ruodai","family":"Cui","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Niu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guosheng","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,10,2]]},"reference":[{"key":"15_CR1","unstructured":"Afifi, M., Derpanis, K.G., Ommer, B., Brown, M.S.: Learning to correct overexposed and underexposed photos. arXiv preprint arXiv:2003.1159613 (2020)"},{"key":"15_CR2","doi-asserted-by":"crossref","unstructured":"Afifi, M., Derpanis, K.G., Ommer, B., Brown, M.S.: Learning multi-scale photo exposure correction. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 9153\u20139163 (2021)","DOI":"10.1109\/CVPR46437.2021.00904"},{"issue":"10","key":"15_CR3","doi-asserted-by":"publisher","first-page":"1647","DOI":"10.1109\/TIP.2005.851684","volume":"14","author":"HA Aly","year":"2005","unstructured":"Aly, H.A., Dubois, E.: Image up-sampling using total-variation regularization with a new observation model. IEEE Trans. Image Process. 14(10), 1647\u20131659 (2005)","journal-title":"IEEE Trans. Image Process."},{"key":"15_CR4","doi-asserted-by":"publisher","first-page":"57942","DOI":"10.1109\/ACCESS.2022.3178698","volume":"10","author":"J Bhattacharya","year":"2022","unstructured":"Bhattacharya, J., Modi, S., Gregorat, L., Ramponi, G.: D2bgan: a dark to bright image conversion model for quality enhancement and analysis tasks without paired supervision. IEEE Access 10, 57942\u201357961 (2022)","journal-title":"IEEE Access"},{"key":"15_CR5","doi-asserted-by":"crossref","unstructured":"Bychkovsky, V., Paris, S., Chan, E., Durand, F.: Learning photographic global tonal adjustment with a database of input\/output image pairs. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 97\u2013104. IEEE (2011)","DOI":"10.1109\/CVPR.2011.5995332"},{"issue":"4","key":"15_CR6","doi-asserted-by":"publisher","first-page":"2049","DOI":"10.1109\/TIP.2018.2794218","volume":"27","author":"J Cai","year":"2018","unstructured":"Cai, J., Gu, S., Zhang, L.: Learning a deep single image contrast enhancer from multi-exposure images. IEEE Trans. Image Process. 27(4), 2049\u20132062 (2018)","journal-title":"IEEE Trans. Image Process."},{"key":"15_CR7","doi-asserted-by":"crossref","unstructured":"Chai, Y., Giryes, R., Wolf, L.: Supervised and unsupervised learning of parameterized color enhancement. In: The IEEE Winter Conference on Applications of Computer Vision (WACV), pp. 992\u20131000 (2020)","DOI":"10.1109\/WACV45572.2020.9093321"},{"key":"15_CR8","doi-asserted-by":"crossref","unstructured":"Chen, Y.S., Wang, Y.C., Kao, M.H., Chuang, Y.Y.: Deep photo enhancer: Unpaired learning for image enhancement from photographs with gans. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 6306\u20136314 (2018)","DOI":"10.1109\/CVPR.2018.00660"},{"key":"15_CR9","doi-asserted-by":"crossref","unstructured":"Choi, Y., Choi, M., Kim, M., Ha, J.W., Kim, S., Choo, J.: Stargan: unified generative adversarial networks for multi-domain image-to-image translation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 8789\u20138797 (2018)","DOI":"10.1109\/CVPR.2018.00916"},{"key":"15_CR10","unstructured":"Dayley, L.D., Dayley, B.: Photoshop CS5 Bible. John Wiley & Sons (2010)"},{"key":"15_CR11","doi-asserted-by":"crossref","unstructured":"Deng, Y., Loy, C., Tang, X.: Aesthetic-driven image enhancement by adversarial learning. In: 2018 ACM Multimedia Conference on Multimedia Conference (MM), pp. 870\u2013878. ACM (2018)","DOI":"10.1145\/3240508.3240531"},{"key":"15_CR12","doi-asserted-by":"crossref","unstructured":"Eyiokur, F.I., Yaman, D., Ekenel, H.K., Waibel, A.: exposure correction model to enhance image quality. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops 2022-June, pp. 675\u2013685 (2022)","DOI":"10.1109\/CVPRW56347.2022.00083"},{"issue":"4","key":"15_CR13","doi-asserted-by":"publisher","first-page":"118","DOI":"10.1145\/3072959.3073592","volume":"36","author":"M Gharbi","year":"2017","unstructured":"Gharbi, M., Chen, J., Barron, J.T., Hasinoff, S.W., Durand, F.: Deep bilateral learning for real-time image enhancement. ACM Trans. Graph. (TOG) 36(4), 118 (2017)","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"15_CR14","doi-asserted-by":"crossref","unstructured":"Guo, C., Li, C., Guo, J., Loy, C., Hou, J., Kwong, S., Cong, R.: Zero-reference deep curve estimation for low-light image enhancement. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1780\u20131789 (2020)","DOI":"10.1109\/CVPR42600.2020.00185"},{"key":"15_CR15","doi-asserted-by":"crossref","unstructured":"He, J., Liu, Y., Qiao, Y., Dong, C.: Conditional sequential modulation for efficient global image retouching. In: European Conference on Computer Vision (ECCV), pp. 679\u2013695. Springer (2020)","DOI":"10.1007\/978-3-030-58601-0_40"},{"issue":"1","key":"15_CR16","doi-asserted-by":"publisher","first-page":"32","DOI":"10.3390\/electronics11010032","volume":"11","author":"S Hu","year":"2021","unstructured":"Hu, S., Yan, J., Deng, D.: Contextual information aided generative adversarial network for low-light image enhancement. Electronics 11(1), 32 (2021)","journal-title":"Electronics"},{"issue":"4","key":"15_CR17","doi-asserted-by":"publisher","first-page":"1752","DOI":"10.1109\/TCE.2007.4429280","volume":"53","author":"H Ibrahim","year":"2007","unstructured":"Ibrahim, H., Kong, N.S.P.: Brightness preserving dynamic histogram equalization for image contrast enhancement. IEEE Trans. Consum. Electron. 53(4), 1752\u20131758 (2007)","journal-title":"IEEE Trans. Consum. Electron."},{"key":"15_CR18","doi-asserted-by":"crossref","unstructured":"Ignatov, A., Kobyshev, N., Timofte, R., Vanhoey, K., Van\u00a0Gool, L.: Dslr-quality photos on mobile devices with deep convolutional networks. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 3277\u20133285 (2017)","DOI":"10.1109\/ICCV.2017.355"},{"key":"15_CR19","doi-asserted-by":"publisher","first-page":"2340","DOI":"10.1109\/TIP.2021.3051462","volume":"30","author":"Y Jiang","year":"2021","unstructured":"Jiang, Y., Gong, X., Liu, D., Cheng, Y., Fang, C., Shen, X., Yang, J., Zhou, P., Wang, Z.: Enlightengan: Deep light enhancement without paired supervision. IEEE Trans. Image Process. 30, 2340\u20132349 (2021)","journal-title":"IEEE Trans. Image Process."},{"key":"15_CR20","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"339","DOI":"10.1007\/978-3-030-58595-2_21","volume-title":"Computer Vision \u2013 ECCV 2020","author":"H-U Kim","year":"2020","unstructured":"Kim, H.-U., Koh, Y.J., Kim, C.-S.: Global and local enhancement networks for paired and unpaired image enhancement. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12370, pp. 339\u2013354. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58595-2_21"},{"key":"15_CR21","doi-asserted-by":"crossref","unstructured":"Kotovenko, D., Sanakoyeu, A., Lang, S., Ommer, B.: Content and style disentanglement for artistic style transfer. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 4422\u20134431 (2019)","DOI":"10.1109\/ICCV.2019.00452"},{"issue":"1","key":"15_CR22","first-page":"1","volume":"61","author":"EH Land","year":"1971","unstructured":"Land, E.H., McCann, J.J.: Lightness and retinex theory. Josa 61(1), 1\u201311 (1971)","journal-title":"Lightness and retinex theory. Josa"},{"key":"15_CR23","unstructured":"Li, C., Guo, C., Ai, Q., Zhou, S., Loy, C.C.: Flexible piecewise curves estimation for photo enhancement. arXiv preprint arXiv:2010.13412 (2020)"},{"key":"15_CR24","unstructured":"Li, C., Guo, C., Feng, R., Zhou, S., Loy, C.C.: Cudi: curve distillation for efficient and controllable exposure adjustment. arXiv preprint arXiv:2207.14273 (2022)"},{"issue":"8","key":"15_CR25","first-page":"4225","volume":"44","author":"C Li","year":"2021","unstructured":"Li, C., Guo, C., Loy, C.C.: Learning to enhance low-light image via zero-reference deep curve estimation. IEEE Trans. Pattern Anal. Mach. Intell. 44(8), 4225\u20134238 (2021)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"15_CR26","doi-asserted-by":"crossref","unstructured":"Liu, E., Li, S., Liu, S.: Color enhancement using global parameters and local features learning. In: Proceedings of the Asian Conference on Computer Vision (2020)","DOI":"10.1007\/978-3-030-69532-3_13"},{"key":"15_CR27","doi-asserted-by":"crossref","unstructured":"Liu, R., Ma, L., Zhang, J., Fan, X., Luo, Z.: Retinex-inspired unrolling with cooperative prior architecture search for low-light image enhancement. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10561\u201310570 (2021)","DOI":"10.1109\/CVPR46437.2021.01042"},{"key":"15_CR28","unstructured":"Liu, Y., et al.: Very lightweight photo retouching network with conditional sequential modulation. CoRR abs\/2104.06279 (2021)"},{"key":"15_CR29","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1016\/j.cviu.2018.10.010","volume":"178","author":"YP Loh","year":"2019","unstructured":"Loh, Y.P., Chan, C.S.: Getting to know low-light images with the exclusively dark dataset. Comput. Vis. Image Underst. 178, 30\u201342 (2019)","journal-title":"Comput. Vis. Image Underst."},{"key":"15_CR30","doi-asserted-by":"crossref","unstructured":"Moran, S., Marza, P., McDonagh, S., Parisot, S., Slabaugh, G.: Deeplpf: Deep local parametric filters for image enhancement. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). pp. 12826\u201312835 (2020)","DOI":"10.1109\/CVPR42600.2020.01284"},{"key":"15_CR31","doi-asserted-by":"crossref","unstructured":"Moran, S., McDonagh, S., Slabaugh, G.: Curl: neural curve layers for global image enhancement. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 9796\u20139803. IEEE (2021)","DOI":"10.1109\/ICPR48806.2021.9412677"},{"key":"15_CR32","unstructured":"Nsampi, N.E., Hu, Z., Wang, Q.: Learning exposure correction via consistency modeling. In: Proc. Brit. Mach. Vision Conf. (2021)"},{"key":"15_CR33","doi-asserted-by":"crossref","unstructured":"Rahman, Z.u., Jobson, D.J., Woodell, G.A.: Retinex processing for automatic image enhancement. J. Electron. imaging 13(1), 100\u2013110 (2004)","DOI":"10.1117\/1.1636183"},{"issue":"9","key":"15_CR34","doi-asserted-by":"publisher","first-page":"4364","DOI":"10.1109\/TIP.2019.2910412","volume":"28","author":"W Ren","year":"2019","unstructured":"Ren, W., et al.: Low-light image enhancement via a deep hybrid network. IEEE Trans. Image Process. 28(9), 4364\u20134375 (2019)","journal-title":"IEEE Trans. Image Process."},{"issue":"3","key":"15_CR35","doi-asserted-by":"publisher","first-page":"8","DOI":"10.4236\/jcc.2019.73002","volume":"7","author":"U Sara","year":"2019","unstructured":"Sara, U., Akter, M., Uddin, M.S.: Image quality assessment through fsim, ssim, mse and psnr-a comparative study. J. Comput. Commun. 7(3), 8\u201318 (2019)","journal-title":"J. Comput. Commun."},{"key":"15_CR36","doi-asserted-by":"publisher","first-page":"68281","DOI":"10.1109\/ACCESS.2022.3186344","volume":"10","author":"X Soria","year":"2022","unstructured":"Soria, X., Pomboza-Junez, G., Sappa, A.D.: Ldc: lightweight dense cnn for edge detection. IEEE Access 10, 68281\u201368290 (2022)","journal-title":"IEEE Access"},{"issue":"4","key":"15_CR37","first-page":"1","volume":"30","author":"B Wang","year":"2011","unstructured":"Wang, B., Yu, Y., Xu, Y.: Example-based image color and tone style enhancement. ACM Trans. Graph. (TOG) 30(4), 1\u201312 (2011)","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"15_CR38","doi-asserted-by":"crossref","unstructured":"Wang, T., et al.: Real-time image enhancer via learnable spatial-aware 3d lookup tables. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 2471\u20132480, October 2021","DOI":"10.1109\/ICCV48922.2021.00247"},{"key":"15_CR39","doi-asserted-by":"crossref","unstructured":"Wang, Y., et al.: Neural color operators for sequential image retouching. In: European Conference on Computer Vision, pp. 38\u201355. Springer (2022)","DOI":"10.1007\/978-3-031-19800-7_3"},{"key":"15_CR40","unstructured":"Wei, C., Wang, W., Yang, W., Liu, J.: Deep retinex decomposition for low-light enhancement. arXiv preprint arXiv:1808.04560 (2018)"},{"issue":"2","key":"15_CR41","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1145\/2790296","volume":"35","author":"Z Yan","year":"2016","unstructured":"Yan, Z., Zhang, H., Wang, B., Paris, S., Yu, Y.: Automatic photo adjustment using deep neural networks. ACM Transactions on Graphics (TOG) 35(2), 11 (2016)","journal-title":"ACM Transactions on Graphics (TOG)"},{"issue":"4","key":"15_CR42","doi-asserted-by":"publisher","first-page":"1022","DOI":"10.1007\/s11263-022-01745-y","volume":"131","author":"KF Yang","year":"2023","unstructured":"Yang, K.F., Cheng, C., Zhao, S.X., Yan, H.M., Zhang, X.S., Li, Y.J.: Learning to adapt to light. Int. J. Comput. Vision 131(4), 1022\u20131041 (2023)","journal-title":"Int. J. Comput. Vision"},{"key":"15_CR43","doi-asserted-by":"crossref","unstructured":"Zeng, H., Cai, J., Li, L., Cao, Z., Zhang, L.: Learning image-adaptive 3d lookup tables for high-performance photo enhancement in real-time. IEEE Trans. Pattern Anal. Mach. Intelli. (TPAMI) (2020)","DOI":"10.1109\/TPAMI.2020.3026740"},{"key":"15_CR44","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Zhang, J., Guo, X.: Kindling the darkness: a practical low-light image enhancer. In: Proceedings of the 27th ACM International Conference on Multimedia, pp. 1632\u20131640 (2019)","DOI":"10.1145\/3343031.3350926"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2024"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-72658-3_15","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,2]],"date-time":"2024-10-02T03:39:31Z","timestamp":1727840371000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-72658-3_15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,2]]},"ISBN":["9783031726576","9783031726583"],"references-count":44,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-72658-3_15","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,10,2]]},"assertion":[{"value":"2 October 2024","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":"Milan","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 September 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2024.ecva.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}