{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T18:31:52Z","timestamp":1743013912757,"version":"3.40.3"},"publisher-location":"Cham","reference-count":22,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030317225"},{"type":"electronic","value":"9783030317232"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-31723-2_65","type":"book-chapter","created":{"date-parts":[[2019,10,31]],"date-time":"2019-10-31T00:05:31Z","timestamp":1572480331000},"page":"761-771","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Dark Channel Prior Guided Conditional Generative Adversarial Network for Single Image Dehazing"],"prefix":"10.1007","author":[{"given":"Yan Zhao","family":"Su","sequence":"first","affiliation":[]},{"given":"Zhi Gao","family":"Cui","sequence":"additional","affiliation":[]},{"given":"Ai Hua","family":"Li","sequence":"additional","affiliation":[]},{"given":"Tao","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Ke","family":"Jiang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,10,31]]},"reference":[{"issue":"8","key":"65_CR1","doi-asserted-by":"publisher","first-page":"3271","DOI":"10.1109\/TIP.2013.2262284","volume":"2","author":"CO Ancuti","year":"2013","unstructured":"Ancuti, C.O., Ancuti, C.: Single image dehazing by multi-scale fusion. IEEE Trans. Image Process. 2(8), 3271\u20133282 (2013)","journal-title":"IEEE Trans. Image Process."},{"key":"65_CR2","doi-asserted-by":"crossref","unstructured":"Tan, R.T.: Visibility in bad weather from a single image. In: Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1\u20138. IEEE, Anchorage (2008)","DOI":"10.1109\/CVPR.2008.4587643"},{"issue":"12","key":"65_CR3","doi-asserted-by":"publisher","first-page":"2341","DOI":"10.1109\/TPAMI.2010.168","volume":"33","author":"K He","year":"2011","unstructured":"He, K., Sun, J., Tang, X.: Single image haze removal using dark channel prior. IEEE Trans. Pattern Anal. Mach. Intell. 33(12), 2341\u20132353 (2011)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"11","key":"65_CR4","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.: A fast single image haze removal algorithm using color attenuation prior. IEEE Trans. Image Process. 24(11), 3522\u20133533 (2015)","journal-title":"IEEE Trans. Image Process."},{"issue":"1","key":"65_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2651362","volume":"34","author":"R Fattal","year":"2014","unstructured":"Fattal, R.: Dehazing using color-lines. ACM Trans. Graph. 34(1), 1\u201314 (2014)","journal-title":"ACM Trans. Graph."},{"key":"65_CR6","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1007\/978-3-319-46475-6_10","volume-title":"ECCV 2016","author":"W Ren","year":"2016","unstructured":"Ren, W., Liu, S., Zhang, H., Pan, J., Cao, X., Yang, M.H.: Single image dehazing via multi-scale convolutional neural networks. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9906, pp. 154\u2013169. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46475-6_10"},{"issue":"11","key":"65_CR7","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.: Dehazenet: An end-to-end system for single image haze removal. IEEE Trans. Image Process. 25(11), 5187\u20135198 (2016)","journal-title":"IEEE Trans. Image Process."},{"key":"65_CR8","doi-asserted-by":"crossref","unstructured":"Zhang, H., Pattel, V.M.: Densely connected pyramid dehazing network. In: Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3194\u20133203. IEEE, Salt Lake City (2018)","DOI":"10.1109\/CVPR.2018.00337"},{"issue":"1","key":"65_CR9","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., et al.: Benchmarking single-image dehazing and beyond. IEEE Trans. Image Process. 28(1), 492\u2013505 (2019)","journal-title":"IEEE Trans. Image Process."},{"key":"65_CR10","series-title":"LNCS","doi-asserted-by":"publisher","first-page":"729","DOI":"10.1007\/978-3-030-01234-2_43","volume-title":"ECCV 2018","author":"D Yang","year":"2018","unstructured":"Yang, D., Sun, J.: Proximal dehaze-net: a prior learning-based deep network for single image dehazing. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11211, pp. 729\u2013746. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01234-2_43"},{"issue":"3","key":"65_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1360612.1360671","volume":"27","author":"R Fattal","year":"2008","unstructured":"Fattal, R.: Single image dehazing. ACM Trans. Graph. (TOG) 27(3), 1\u20138 (2008)","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"65_CR12","doi-asserted-by":"crossref","unstructured":"Berman, D., Avidan, S., et al.: Non-local image dehazing. In: Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1674\u20131682. IEEE, Las Vegas (2016)","DOI":"10.1109\/CVPR.2016.185"},{"key":"65_CR13","doi-asserted-by":"crossref","unstructured":"Li, B., Peng, X., Wang, Z., Xu, J., Feng, D.: AOD-Net: all-in-one dehazing network. In: IEEE International Conference on Computer Vision (ICCV), pp. 4770\u20134778. IEEE, Venice (2017)","DOI":"10.1109\/ICCV.2017.511"},{"key":"65_CR14","doi-asserted-by":"crossref","unstructured":"Du, Y., Li, X.: Recursive deep residual learning for single image dehazing. In: Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), pp. 730\u2013737. IEEE, Salt Lake City (2018)","DOI":"10.1109\/CVPRW.2018.00116"},{"key":"65_CR15","doi-asserted-by":"crossref","unstructured":"Ren, W., et al.: Gated fusion network for single image dehazing. In: Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3253\u20133261. IEEE, Salt Lake City (2018)","DOI":"10.1109\/CVPR.2018.00343"},{"key":"65_CR16","unstructured":"Goodfellow, I., et al.: Generative adversarial nets. In: 27th International Conference on Neural Information Processing Systems, pp. 2672\u20132680. MIT Press (2014)"},{"key":"65_CR17","doi-asserted-by":"crossref","unstructured":"Zhu, H., Peng, X., Chandrasekhar, V., et al.: DehazeGAN: when image dehazing meets differential programming. In: 27th International Joint Conference on Artificial Intelligence, pp. 1234\u20131240. AAAI Press (2018)","DOI":"10.24963\/ijcai.2018\/172"},{"key":"65_CR18","doi-asserted-by":"crossref","unstructured":"Yang, X., Xu, Z., Luo, J.: Towards perceptual image dehazing by physics-based disentanglement and adversarial training. In: Thirty-Second AAAI Conference on Artificial Intelligence (2018)","DOI":"10.1609\/aaai.v32i1.12317"},{"key":"65_CR19","doi-asserted-by":"crossref","unstructured":"Li, R., Pan, J., Li, Z., Tang, J.: Single image dehazing via conditional generative adversarial network. In: Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), pp. 8202\u20138211. IEEE, Salt Lake City (2018)","DOI":"10.1109\/CVPR.2018.00856"},{"key":"65_CR20","doi-asserted-by":"crossref","unstructured":"Wang, T., Liu, M., Zhu, J., Tao, A., Kautz, J., Catanzaro, B.: High-resolution image synthesis and semantic manipulation with conditional GANs. In: Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), pp. 8798\u20138807. IEEE, Salt Lake City (2018)","DOI":"10.1109\/CVPR.2018.00917"},{"key":"65_CR21","unstructured":"Kingma, D., Ba, J.: Adam: a method for stochastic optimization. In: 3rd International Conference on Learning Representations (ICLR), San Diego, CA, USA (2015)"},{"key":"65_CR22","doi-asserted-by":"crossref","unstructured":"Isola, P., Zhu, J.-Y., Zhou, T., Efros, A.A.: Image-to-image translation with conditional adversarial networks. In: Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1125\u20131134. IEEE, Honolulu (2017)","DOI":"10.1109\/CVPR.2017.632"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition and Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-31723-2_65","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T00:29:26Z","timestamp":1730334566000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-31723-2_65"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030317225","9783030317232"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-31723-2_65","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"31 October 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chinese Conference on Pattern Recognition and Computer Vision  (PRCV)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Xi'an","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 November 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 November 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ccprcv2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.prcv2019.com\/en\/index.html","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":"412","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":"165","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":"40% - 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":"4","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":"4","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}