{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T04:00:31Z","timestamp":1777003231518,"version":"3.51.4"},"publisher-location":"Singapore","reference-count":29,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819786916","type":"print"},{"value":"9789819786923","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T00:00:00Z","timestamp":1730419200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T00:00:00Z","timestamp":1730419200000},"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\/978-981-97-8692-3_4","type":"book-chapter","created":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T14:03:04Z","timestamp":1730383384000},"page":"42-55","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Two-Branch Fusion Network for\u00a0Infrared and\u00a0Visible Image Fusion"],"prefix":"10.1007","author":[{"given":"Weihao","family":"Zhang","sequence":"first","affiliation":[]},{"given":"Zhilin","family":"Li","sequence":"additional","affiliation":[]},{"given":"Bin","family":"Li","sequence":"additional","affiliation":[]},{"given":"Mingliang","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,11,1]]},"reference":[{"issue":"3","key":"4_CR1","doi-asserted-by":"publisher","first-page":"880","DOI":"10.1016\/j.patcog.2007.06.022","volume":"41","author":"R Singh","year":"2008","unstructured":"Singh, R., Vatsa, M., Noore, A.: Integrated multilevel image fusion and match score fusion of visible and infrared face images for robust face recognition. Pattern Recogn. 41(3), 880\u2013893 (2008)","journal-title":"Pattern Recogn."},{"issue":"6","key":"4_CR2","doi-asserted-by":"publisher","first-page":"1771","DOI":"10.1016\/j.patcog.2006.11.010","volume":"40","author":"J Han","year":"2007","unstructured":"Han, J., Bhanu, B.: Fusion of color and infrared video for moving human detection. Pattern Recogn. 40(6), 1771\u20131784 (2007)","journal-title":"Pattern Recogn."},{"key":"4_CR3","doi-asserted-by":"crossref","unstructured":"Reinhard, E., et al.: Color transfer between images. Comput. Graph. Appl. 21(5), 34\u201341 (2001)","DOI":"10.1109\/38.946629"},{"key":"4_CR4","doi-asserted-by":"crossref","unstructured":"Bulanon, D.M., Burks, T., F. Alchanatis, V.: Image fusion of visible and thermal images for fruit detection. Biosyst. Eng. 103(1), 12\u201322 (2009)","DOI":"10.1016\/j.biosystemseng.2009.02.009"},{"issue":"4","key":"4_CR5","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1016\/0167-8655(89)90003-2","volume":"9","author":"A Toet","year":"1989","unstructured":"Toet, A.: Image fusion by a ratio of low-pass pyramid. Pattern Recogn. Lett. 9(4), 245\u2013253 (1989)","journal-title":"Pattern Recogn. Lett."},{"key":"4_CR6","doi-asserted-by":"crossref","unstructured":"Liu, C.H., Qi, Y., Ding, W.R.: Infrared and visible image fusion method based on saliency detection in sparse domain. Infrared Phys. Technol. 83, 94\u2013102 (2017)","DOI":"10.1016\/j.infrared.2017.04.018"},{"key":"4_CR7","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems, pp. 1\u201315 (2017)"},{"key":"4_CR8","doi-asserted-by":"crossref","unstructured":"Ma, J., et al.: FusionGAN: a generative adversarial network for infrared and visible image fusion. Inf. Fusion 48, 11\u201326 (2019)","DOI":"10.1016\/j.inffus.2018.09.004"},{"key":"4_CR9","doi-asserted-by":"crossref","unstructured":"Li, J., et al.: AttentionFGAN: infrared and visible image fusion using attention-based generative adversarial networks. IEEE Trans. Multimed. 23, 1383\u20131396 (2020)","DOI":"10.1109\/TMM.2020.2997127"},{"key":"4_CR10","doi-asserted-by":"crossref","unstructured":"Liu, J., et al.: Learning a deep multi-scale feature ensemble and an edge-attention guidance for image fusion. IEEE Trans. Circuits Syst. Video Technol. 32(1), 105\u2013119 (2021)","DOI":"10.1109\/TCSVT.2021.3056725"},{"key":"4_CR11","doi-asserted-by":"crossref","unstructured":"Liu, J., et al.: Target-aware dual adversarial learning and a multi-scenario multi-modality benchmark to fuse infrared and visible for object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5802\u20135811 (2022)","DOI":"10.1109\/CVPR52688.2022.00571"},{"key":"4_CR12","doi-asserted-by":"crossref","unstructured":"Li, H., Wu, X.J., Kittler, J.: Infrared and visible image fusion using a deep learning framework. In: International Conference on Pattern Recognition, pp. 2705\u20132710 (2018)","DOI":"10.1109\/ICPR.2018.8546006"},{"issue":"5","key":"4_CR13","doi-asserted-by":"publisher","first-page":"2614","DOI":"10.1109\/TIP.2018.2887342","volume":"28","author":"H Li","year":"2018","unstructured":"Li, H., Wu, X.J.: DenseFuse: a fusion approach to infrared and visible images. IEEE Trans. Image Process. 28(5), 2614\u20132623 (2018)","journal-title":"IEEE Trans. Image Process."},{"key":"4_CR14","doi-asserted-by":"crossref","unstructured":"Zhao, Z., et al.: DIDFuse: deep image decomposition for infrared and visible image fusion. In: International Joint Conference on Artificial Intelligence, pp. 970\u2013976 (2020)","DOI":"10.24963\/ijcai.2020\/135"},{"key":"4_CR15","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1016\/j.inffus.2021.12.004","volume":"82","author":"L Tang","year":"2022","unstructured":"Tang, L., Yuan, J., Ma, J.: Image fusion in the loop of high-level vision tasks: a semantic-aware real-time infrared and visible image fusion network. Inf. Fusion 82, 28\u201342 (2022)","journal-title":"Inf. Fusion"},{"key":"4_CR16","doi-asserted-by":"crossref","unstructured":"Liu, J., Liu, Z., Wu, G.: Multi-interactive feature learning and a full-time multi-modality benchmark for image fusion and segmentation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 8115\u20138124 (2023)","DOI":"10.1109\/ICCV51070.2023.00745"},{"key":"4_CR17","doi-asserted-by":"crossref","unstructured":"Wang, Z., et al.: SwinFuse: a residual swin transformer fusion network for infrared and visible images. IEEE Trans. Instrum. Meas. 71, 1\u201312 (2022)","DOI":"10.1109\/TIM.2022.3191664"},{"key":"4_CR18","doi-asserted-by":"crossref","unstructured":"Ma, J., et al.: SwinFusion: cross-domain long-range learning for general image fusion via swin transformer. IEEE\/CAA J. Autom. Sin. 9(7), 1200\u20131217 (2022)","DOI":"10.1109\/JAS.2022.105686"},{"key":"4_CR19","doi-asserted-by":"crossref","unstructured":"Zhao, Z., et al.: CDDFuse: correlation-driven dual-branch feature decomposition for multi-modality image fusion. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5906\u20135916 (2023)","DOI":"10.1109\/CVPR52729.2023.00572"},{"key":"4_CR20","unstructured":"Dinh, L., Sohl-Dickstein, J., Bengio, S.: Density estimation using real NVP. In: International Conference on Learning Representations, pp. 1\u201332 (2016)"},{"key":"4_CR21","doi-asserted-by":"crossref","unstructured":"Woo, S., et al.: CBAM: convolutional block attention module. In: Proceedings of the European Conference on Computer Vision, pp. 3\u201319 (2018)","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"4_CR22","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1016\/j.inffus.2022.03.007","volume":"83","author":"L Tang","year":"2022","unstructured":"Tang, L., Yuan, J., Zhang, H., et al.: PIAFusion: a progressive infrared and visible image fusion network based on illumination aware. Inf. Fusion 83, 79\u201392 (2022)","journal-title":"Inf. Fusion"},{"key":"4_CR23","doi-asserted-by":"crossref","unstructured":"Xu, H., et al.: FusionDN: a unified densely connected network for image fusion. In: Proceedings of the AAAI Conference on Artificial Intelligence, pp. 12484\u201312491 (2020)","DOI":"10.1609\/aaai.v34i07.6936"},{"issue":"1","key":"4_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1117\/1.OE.51.1.010901","volume":"51","author":"A Toet","year":"2012","unstructured":"Toet, A., Hogervorst, M.A.: Progress in color night vision. Opt. Eng. 51(1), 1\u201320 (2012)","journal-title":"Opt. Eng."},{"key":"4_CR25","doi-asserted-by":"crossref","unstructured":"Zamir, S.W., et al.: Restormer: efficient transformer for high-resolution image restoration. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5718\u20135729 (2022)","DOI":"10.1109\/CVPR52688.2022.00564"},{"key":"4_CR26","doi-asserted-by":"crossref","unstructured":"Li, H., Wu, X, J., Kittler, J.: RFN-Nest: an end-to-end residual fusion network for infrared and visible images. Inf. Fusion 73, 72\u201386 (2021)","DOI":"10.1016\/j.inffus.2021.02.023"},{"key":"4_CR27","doi-asserted-by":"crossref","unstructured":"Zhang, Y., et al.: IFCNN: a general image fusion framework based on convolutional neural network. Inf. Fusion 54, 99\u2013118 (2020)","DOI":"10.1016\/j.inffus.2019.07.011"},{"key":"4_CR28","doi-asserted-by":"crossref","unstructured":"Xu, H., et al.: U2Fusion: a unified unsupervised image fusion network. IEEE Trans. Pattern Anal. Mach. Intell. 44(1), 502\u2013518 (2020)","DOI":"10.1109\/TPAMI.2020.3012548"},{"key":"4_CR29","doi-asserted-by":"crossref","unstructured":"Liang, P., et al.: Fusion from decomposition: a self-supervised decomposition approach for image fusion. In: Proceedings of the European Conference on Computer Vision, pp. 719\u2013735 (2022)","DOI":"10.1007\/978-3-031-19797-0_41"}],"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\/978-981-97-8692-3_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,31]],"date-time":"2024-10-31T14:22:51Z","timestamp":1730384571000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-8692-3_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,1]]},"ISBN":["9789819786916","9789819786923"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-8692-3_4","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,1]]},"assertion":[{"value":"1 November 2024","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":"Urumqi","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":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 October 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ccprcv2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2024.prcv.cn\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}