{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T16:49:54Z","timestamp":1777567794168,"version":"3.51.4"},"publisher-location":"Cham","reference-count":42,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031200670","type":"print"},{"value":"9783031200687","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\/978-3-031-20068-7_29","type":"book-chapter","created":{"date-parts":[[2022,11,10]],"date-time":"2022-11-10T08:06:38Z","timestamp":1668067598000},"page":"505-521","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Semantic-Sparse Colorization Network for\u00a0Deep Exemplar-Based Colorization"],"prefix":"10.1007","author":[{"given":"Yunpeng","family":"Bai","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chao","family":"Dong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3709-4947","authenticated-orcid":false,"given":"Zenghao","family":"Chai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhengzhuo","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chun","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,11,11]]},"reference":[{"key":"29_CR1","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"443","DOI":"10.1007\/978-3-030-01258-8_27","volume-title":"Computer Vision \u2013 ECCV 2018","author":"H Bahng","year":"2018","unstructured":"Bahng, H., et al.: Coloring with words: guiding image colorization through text-based palette generation. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11216, pp. 443\u2013459. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01258-8_27"},{"issue":"1","key":"29_CR2","doi-asserted-by":"publisher","first-page":"298","DOI":"10.1109\/TIP.2013.2288929","volume":"23","author":"A Bugeau","year":"2014","unstructured":"Bugeau, A., Ta, V., Papadakis, N.: Variational exemplar-based image colorization. IEEE Trans. Image Process. 23(1), 298\u2013307 (2014)","journal-title":"IEEE Trans. Image Process."},{"key":"29_CR3","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1007\/978-3-319-71249-9_10","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"Y Cao","year":"2017","unstructured":"Cao, Y., Zhou, Z., Zhang, W., Yu, Y.: Unsupervised diverse colorization via generative adversarial networks. In: Ceci, M., Hollm\u00e9n, J., Todorovski, L., Vens, C., D\u017eeroski, S. (eds.) ECML PKDD 2017. LNCS (LNAI), vol. 10534, pp. 151\u2013166. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-71249-9_10"},{"key":"29_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"126","DOI":"10.1007\/978-3-540-88690-7_10","volume-title":"Computer Vision \u2013 ECCV 2008","author":"G Charpiat","year":"2008","unstructured":"Charpiat, G., Hofmann, M., Sch\u00f6lkopf, B.: Automatic image colorization via multimodal predictions. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008. LNCS, vol. 5304, pp. 126\u2013139. Springer, Heidelberg (2008). https:\/\/doi.org\/10.1007\/978-3-540-88690-7_10"},{"key":"29_CR5","doi-asserted-by":"crossref","unstructured":"Cheng, Z., Yang, Q., Sheng, B.: Deep colorization. In: ICCV 2015, pp. 415\u2013423. IEEE Computer Society (2015)","DOI":"10.1109\/ICCV.2015.55"},{"issue":"6","key":"29_CR6","doi-asserted-by":"publisher","first-page":"156","DOI":"10.1145\/2070781.2024190","volume":"30","author":"AYS Chia","year":"2011","unstructured":"Chia, A.Y.S., et al.: Semantic colorization with internet images. ACM Trans. Graph. 30(6), 156 (2011)","journal-title":"ACM Trans. Graph."},{"key":"29_CR7","doi-asserted-by":"crossref","unstructured":"Ci, Y., Ma, X., Wang, Z., Li, H., Luo, Z.: User-guided deep anime line art colorization with conditional adversarial networks. In: MM 2018, pp. 1536\u20131544. ACM (2018)","DOI":"10.1145\/3240508.3240661"},{"key":"29_CR8","doi-asserted-by":"crossref","unstructured":"Deng, J., Dong, W., Socher, R., Li, L., Li, K., Li, F.: Imagenet: a large-scale hierarchical image database. In: CVPR 2009, pp. 248\u2013255. IEEE Computer Society (2009)","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"29_CR9","doi-asserted-by":"crossref","unstructured":"Deshpande, A., Lu, J., Yeh, M., Chong, M.J., Forsyth, D.A.: Learning diverse image colorization. In: CVPR 2017, pp. 2877\u20132885. IEEE Computer Society (2017)","DOI":"10.1109\/CVPR.2017.307"},{"key":"29_CR10","doi-asserted-by":"crossref","unstructured":"Gupta, R.K., Chia, A.Y.S., Rajan, D., Ng, E.S., Huang, Z.: Image colorization using similar images. In: MM 2012, pp. 369\u2013378. ACM (2012)","DOI":"10.1145\/2393347.2393402"},{"key":"29_CR11","doi-asserted-by":"crossref","unstructured":"He, M., Chen, D., Liao, J., Sander, P.V., Yuan, L.: Deep exemplar-based colorization. ACM Trans. Graph. 37(4), 47:1\u201347:16 (2018)","DOI":"10.1145\/3197517.3201365"},{"key":"29_CR12","doi-asserted-by":"crossref","unstructured":"Huang, X., Belongie, S.J.: Arbitrary style transfer in real-time with adaptive instance normalization. In: IEEE International Conference on Computer Vision, ICCV 2017, Venice, Italy, 22\u201329 October 2017, pp. 1510\u20131519. IEEE Computer Society (2017)","DOI":"10.1109\/ICCV.2017.167"},{"key":"29_CR13","doi-asserted-by":"crossref","unstructured":"Huang, Y., Tung, Y., Chen, J., Wang, S., Wu, J.: An adaptive edge detection based colorization algorithm and its applications. In: MM 2005, pp. 351\u2013354. ACM (2005)","DOI":"10.1145\/1101149.1101223"},{"key":"29_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"694","DOI":"10.1007\/978-3-319-46475-6_43","volume-title":"Computer Vision \u2013 ECCV 2016","author":"J Johnson","year":"2016","unstructured":"Johnson, J., Alahi, A., Fei-Fei, L.: Perceptual losses for real-time style transfer and super-resolution. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9906, pp. 694\u2013711. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46475-6_43"},{"key":"29_CR15","doi-asserted-by":"crossref","unstructured":"Karras, T., Laine, S., Aila, T.: A style-based generator architecture for generative adversarial networks. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2019, Long Beach, CA, USA, 16\u201320 June 2019, pp. 4401\u20134410. Computer Vision Foundation\/IEEE (2019)","DOI":"10.1109\/CVPR.2019.00453"},{"key":"29_CR16","doi-asserted-by":"crossref","unstructured":"Kim, E., Lee, S., Park, J., Choi, S., Seo, C., Choo, J.: Deep edge-aware interactive colorization against color-bleeding effects. CoRR (2021)","DOI":"10.1109\/ICCV48922.2021.01440"},{"key":"29_CR17","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. In: ICLR 2015 (2015)"},{"key":"29_CR18","unstructured":"Kumar, M., Weissenborn, D., Kalchbrenner, N.: Colorization transformer. CoRR arXiv:2102.04432 (2021)"},{"key":"29_CR19","doi-asserted-by":"crossref","unstructured":"Lee, J., Kim, E., Lee, Y., Kim, D., Chang, J., Choo, J.: Reference-based sketch image colorization using augmented-self reference and dense semantic correspondence. In: CVPR 2020, pp. 5800\u20135809. IEEE Computer Society (2020)","DOI":"10.1109\/CVPR42600.2020.00584"},{"issue":"3","key":"29_CR20","doi-asserted-by":"publisher","first-page":"689","DOI":"10.1145\/1015706.1015780","volume":"23","author":"A Levin","year":"2004","unstructured":"Levin, A., Lischinski, D., Weiss, Y.: Colorization using optimization. ACM Trans. Graph. 23(3), 689\u2013694 (2004)","journal-title":"ACM Trans. Graph."},{"key":"29_CR21","doi-asserted-by":"publisher","first-page":"8526","DOI":"10.1109\/TIP.2021.3117061","volume":"30","author":"H Li","year":"2021","unstructured":"Li, H., Sheng, B., Li, P., Ali, R., Chen, C.L.P.: Globally and locally semantic colorization via exemplar-based broad-GAN. IEEE Trans. Image Process. 30, 8526\u20138539 (2021)","journal-title":"IEEE Trans. Image Process."},{"key":"29_CR22","doi-asserted-by":"crossref","unstructured":"Liao, J., Yao, Y., Yuan, L., Hua, G., Kang, S.B.: Visual attribute transfer through deep image analogy. ACM Trans. Graph. 36(4), 120:1\u2013120:15 (2017)","DOI":"10.1145\/3072959.3073683"},{"key":"29_CR23","doi-asserted-by":"crossref","unstructured":"Lu, P., Yu, J., Peng, X., Zhao, Z., Wang, X.: Gray2colornet: transfer more colors from reference image. In: MM 2020, pp. 3210\u20133218. ACM (2020)","DOI":"10.1145\/3394171.3413594"},{"key":"29_CR24","unstructured":"Luan, Q., Wen, F., Cohen-Or, D., Liang, L., Xu, Y., Shum, H.: Natural image colorization. In: Proceedings of the Eurographics Symposium on Rendering Techniques 2007, pp. 309\u2013320. Eurographics Association (2007)"},{"key":"29_CR25","doi-asserted-by":"crossref","unstructured":"Manjunatha, V., Iyyer, M., Boyd-Graber, J.L., Davis, L.S.: Learning to color from language. In: NAACL-HLT 2018, pp. 764\u2013769. Association for Computational Linguistics (2018)","DOI":"10.18653\/v1\/N18-2120"},{"issue":"3","key":"29_CR26","doi-asserted-by":"publisher","first-page":"1214","DOI":"10.1145\/1141911.1142017","volume":"25","author":"Y Qu","year":"2006","unstructured":"Qu, Y., Wong, T., Heng, P.: Manga colorization. ACM Trans. Graph. 25(3), 1214\u20131220 (2006)","journal-title":"ACM Trans. Graph."},{"key":"29_CR27","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1007\/978-3-319-24574-4_28","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015","author":"O Ronneberger","year":"2015","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-Net: convolutional networks for biomedical image segmentation. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9351, pp. 234\u2013241. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28"},{"key":"29_CR28","doi-asserted-by":"crossref","unstructured":"Sangkloy, P., Lu, J., Fang, C., Yu, F., Hays, J.: Scribbler: controlling deep image synthesis with sketch and color. In: CVPR 2017, pp. 6836\u20136845. IEEE Computer Society (2017)","DOI":"10.1109\/CVPR.2017.723"},{"key":"29_CR29","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. In: ICLR 2015 (2015)"},{"key":"29_CR30","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, pp. 5998\u20136008 (2017)"},{"key":"29_CR31","doi-asserted-by":"crossref","unstructured":"Vitoria, P., Raad, L., Ballester, C.: Chromagan: adversarial picture colorization with semantic class distribution. In: WACV 2020, pp. 2434\u20132443. IEEE (2020)","DOI":"10.1109\/WACV45572.2020.9093389"},{"key":"29_CR32","doi-asserted-by":"crossref","unstructured":"Wu, Y., Wang, X., Li, Y., Zhang, H., Zhao, X., Shan, Y.: Towards vivid and diverse image colorization with generative color prior. CoRR (2021)","DOI":"10.1109\/ICCV48922.2021.01411"},{"issue":"1","key":"29_CR33","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1111\/cgf.13659","volume":"39","author":"C Xiao","year":"2020","unstructured":"Xiao, C., et al.: Example-based colourization via dense encoding pyramids. Comput. Graph. Forum 39(1), 20\u201333 (2020)","journal-title":"Comput. Graph. Forum"},{"issue":"5","key":"29_CR34","doi-asserted-by":"publisher","first-page":"118","DOI":"10.1145\/1618452.1618464","volume":"28","author":"K Xu","year":"2009","unstructured":"Xu, K., Li, Y., Ju, T., Hu, S., Liu, T.: Efficient affinity-based edit propagation using K-D tree. ACM Trans. Graph. 28(5), 118 (2009)","journal-title":"ACM Trans. Graph."},{"key":"29_CR35","doi-asserted-by":"crossref","unstructured":"Xu, Z., Wang, T., Fang, F., Sheng, Y., Zhang, G.: Stylization-based architecture for fast deep exemplar colorization. In: CVPR 2020, pp. 9360\u20139369. IEEE (2020)","DOI":"10.1109\/CVPR42600.2020.00938"},{"key":"29_CR36","unstructured":"Yin, W., Lu, P., Zhao, Z., Peng, X.: Yes, \u201cattention is all you need\u201d, for exemplar based colorization. In: MM 2021: ACM Multimedia Conference, Virtual Event, China, 20\u201324 October 2021, pp. 2243\u20132251. ACM (2021)"},{"key":"29_CR37","doi-asserted-by":"crossref","unstructured":"Yoo, S., Bahng, H., Chung, S., Lee, J., Chang, J., Choo, J.: Coloring with limited data: few-shot colorization via memory augmented networks. In: CVPR 2019, pp. 11283\u201311292. Computer Vision Foundation\/IEEE (2019)","DOI":"10.1109\/CVPR.2019.01154"},{"key":"29_CR38","doi-asserted-by":"crossref","unstructured":"Zhang, B., et al.: Deep exemplar-based video colorization. In: CVPR 2019, pp. 8052\u20138061. Computer Vision Foundation\/IEEE (2019)","DOI":"10.1109\/CVPR.2019.00824"},{"key":"29_CR39","doi-asserted-by":"crossref","unstructured":"Zhang, J., et al.: Scsnet: an efficient paradigm for learning simultaneously image colorization and super-resolution. CoRR (2022)","DOI":"10.1609\/aaai.v36i3.20236"},{"key":"29_CR40","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"649","DOI":"10.1007\/978-3-319-46487-9_40","volume-title":"Computer Vision \u2013 ECCV 2016","author":"R Zhang","year":"2016","unstructured":"Zhang, R., Isola, P., Efros, A.A.: Colorful image colorization. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9907, pp. 649\u2013666. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46487-9_40"},{"key":"29_CR41","doi-asserted-by":"crossref","unstructured":"Zhang, R., et al.: Real-time user-guided image colorization with learned deep priors. ACM Trans. Graph. 36(4), 119:1\u2013119:11 (2017)","DOI":"10.1145\/3072959.3073703"},{"key":"29_CR42","doi-asserted-by":"crossref","unstructured":"Zhou, B., Khosla, A., Lapedriza, \u00c0., Oliva, A., Torralba, A.: Learning deep features for discriminative localization. In: CVPR 2016, pp. 2921\u20132929. IEEE Computer Society (2016)","DOI":"10.1109\/CVPR.2016.319"}],"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\/978-3-031-20068-7_29","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,10]],"date-time":"2022-11-10T08:18:11Z","timestamp":1668068291000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-20068-7_29"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031200670","9783031200687"],"references-count":42,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-20068-7_29","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":"11 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)"}}]}}