{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T05:48:00Z","timestamp":1784008080874,"version":"3.55.0"},"publisher-location":"New York, NY, USA","reference-count":42,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,10,17]],"date-time":"2021-10-17T00:00:00Z","timestamp":1634428800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"National Natural Science Foundation of China","award":["61702083"],"award-info":[{"award-number":["61702083"]}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2020YFA0714001"],"award-info":[{"award-number":["2020YFA0714001"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key Projects of Applied Basic Research in Sichuan Province","award":["2020YJ0216"],"award-info":[{"award-number":["2020YJ0216"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,10,17]]},"DOI":"10.1145\/3474085.3475600","type":"proceedings-article","created":{"date-parts":[[2021,10,18]],"date-time":"2021-10-18T06:57:34Z","timestamp":1634540254000},"page":"4472-4480","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":68,"title":["SSconv"],"prefix":"10.1145","author":[{"given":"Yudong","family":"Wang","sequence":"first","affiliation":[{"name":"University of Electronic Science and Technology of China, Chengdu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liang-Jian","family":"Deng","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China, Chengdu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tian-Jing","family":"Zhang","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China, Chengdu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiao","family":"Wu","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China, Chengdu, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2021,10,17]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2002.803623"},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.14358\/PERS.72.5.591"},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2007.904923"},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2007.904923"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2010.2051674"},{"key":"e_1_3_2_2_6_1","volume-title":"International conference on medical image computing and computer-assisted intervention. Springer, 424--432","author":"\u0106i\u00e7ek \u00f6zg\u00fcn","year":"2016","unstructured":"\u00f6zg\u00fcn \u0106i\u00e7ek , Ahmed Abdulkadir , Soeren S Lienkamp , Thomas Brox , and Olaf Ronneberger . 2016 . 3D U-Net: learning dense volumetric segmentation from sparse annotation . In International conference on medical image computing and computer-assisted intervention. Springer, 424--432 . \u00f6zg\u00fcn \u0106i\u00e7ek, Ahmed Abdulkadir, Soeren S Lienkamp, Thomas Brox, and Olaf Ronneberger. 2016. 3D U-Net: learning dense volumetric segmentation from sparse annotation. In International conference on medical image computing and computer-assisted intervention. Springer, 424--432."},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2015.2462751"},{"key":"e_1_3_2_2_8_1","volume-title":"Detail Injection-Based Deep Convolutional Neural Networks for Pansharpening","author":"Deng Liang-Jian","year":"2020","unstructured":"Liang-Jian Deng , Gemine Vivone , Cheng Jin , and Jocelyn Chanussot . 2020. Detail Injection-Based Deep Convolutional Neural Networks for Pansharpening . IEEE Transactions on Geoscience and Remote Sensing ( 2020 ). Liang-Jian Deng, Gemine Vivone, Cheng Jin, and Jocelyn Chanussot. 2020. Detail Injection-Based Deep Convolutional Neural Networks for Pansharpening. IEEE Transactions on Geoscience and Remote Sensing (2020)."},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2996498"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2009.2022650"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2007.907604"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7299173"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2019.2898574"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3351084"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2020.03.006"},{"key":"e_1_3_2_2_16_1","volume-title":"Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980","author":"Kingma Diederik P","year":"2014","unstructured":"Diederik P Kingma and Jimmy Ba . 2014 . Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014). Diederik P Kingma and Jimmy Ba. 2014. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)."},{"key":"e_1_3_2_2_17_1","volume-title":"Imagenet classification with deep convolutional neural networks. Advances in neural information processing systems","author":"Krizhevsky Alex","year":"2012","unstructured":"Alex Krizhevsky , Ilya Sutskever , and Geoffrey E Hinton . 2012. Imagenet classification with deep convolutional neural networks. Advances in neural information processing systems , Vol. 25 ( 2012 ), 1097--1105. Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. 2012. Imagenet classification with deep convolutional neural networks. Advances in neural information processing systems, Vol. 25 (2012), 1097--1105."},{"key":"e_1_3_2_2_18_1","first-page":"011","article-title":"Process for enhancing the spatial resolution of multispectral imagery using pan-sharpening","volume":"6","author":"Laben Craig A","year":"2000","unstructured":"Craig A Laben and Bernard V Brower . 2000 . Process for enhancing the spatial resolution of multispectral imagery using pan-sharpening . US Patent 6 , 011 ,875. Craig A Laben and Bernard V Brower. 2000. Process for enhancing the spatial resolution of multispectral imagery using pan-sharpening. US Patent 6,011,875.","journal-title":"US Patent"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1080\/014311600750037499"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.3390\/rs8070594"},{"key":"e_1_3_2_2_22_1","volume-title":"Spectral normalization for generative adversarial networks. arXiv preprint arXiv:1802.05957","author":"Miyato Takeru","year":"2018","unstructured":"Takeru Miyato , Toshiki Kataoka , Masanori Koyama , and Yuichi Yoshida . 2018. Spectral normalization for generative adversarial networks. arXiv preprint arXiv:1802.05957 ( 2018 ). Takeru Miyato, Toshiki Kataoka, Masanori Koyama, and Yuichi Yoshida. 2018. Spectral normalization for generative adversarial networks. arXiv preprint arXiv:1802.05957 (2018)."},{"key":"e_1_3_2_2_23_1","volume-title":"Matthew Lee, Mattias Heinrich, Kazunari Misawa, Kensaku Mori, Steven McDonagh, Nils Y Hammerla","author":"Oktay Ozan","year":"2018","unstructured":"Ozan Oktay , Jo Schlemper , Loic Le Folgoc , Matthew Lee, Mattias Heinrich, Kazunari Misawa, Kensaku Mori, Steven McDonagh, Nils Y Hammerla , Bernhard Kainz , et almbox. 2018 . Attention u-net: Learning where to look for the pancreas. arXiv preprint arXiv:1804.03999 (2018). Ozan Oktay, Jo Schlemper, Loic Le Folgoc, Matthew Lee, Mattias Heinrich, Kazunari Misawa, Kensaku Mori, Steven McDonagh, Nils Y Hammerla, Bernhard Kainz, et almbox. 2018. Attention u-net: Learning where to look for the pancreas. arXiv preprint arXiv:1804.03999 (2018)."},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.207"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3126686.3126727"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2007.912448"},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2019.2906073"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2014.2361734"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2014.2361734"},{"key":"e_1_3_2_2_31_1","volume-title":"Andrea Garzelli, Rocco Restaino, Giuseppe Scarpa, Magnus Orn Ulfarsson, Luciano Alparone, and Jocelyn Chanussot.","author":"Vivone Gemine","year":"2020","unstructured":"Gemine Vivone , Mauro Dalla Mura , Andrea Garzelli, Rocco Restaino, Giuseppe Scarpa, Magnus Orn Ulfarsson, Luciano Alparone, and Jocelyn Chanussot. 2020 . A New Benchmark Based on Recent Advances in Multispectral Pansharpening : Revisiting pansharpening with classical and emerging pansharpening methods. IEEE Geoscience and Remote Sensing Magazine ( 2020). Gemine Vivone, Mauro Dalla Mura, Andrea Garzelli, Rocco Restaino, Giuseppe Scarpa, Magnus Orn Ulfarsson, Luciano Alparone, and Jocelyn Chanussot. 2020. A New Benchmark Based on Recent Advances in Multispectral Pansharpening: Revisiting pansharpening with classical and emerging pansharpening methods. IEEE Geoscience and Remote Sensing Magazine (2020)."},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2013.2281996"},{"key":"e_1_3_2_2_33_1","unstructured":"Lucien Wald. 2002. Data fusion: definitions and architectures: fusion of images of different spatial resolutions. Presses des MINES.  Lucien Wald. 2002. Data fusion: definitions and architectures: fusion of images of different spatial resolutions. Presses des MINES."},{"key":"e_1_3_2_2_34_1","volume-title":"A universal image quality index","author":"Wang Zhou","year":"2002","unstructured":"Zhou Wang and Alan C Bovik . 2002. A universal image quality index . IEEE signal processing letters, Vol. 9 , 3 ( 2002 ), 81--84. Zhou Wang and Alan C Bovik. 2002. A universal image quality index. IEEE signal processing letters, Vol. 9, 3 (2002), 81--84."},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.5555\/3454287.3454395"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.193"},{"key":"e_1_3_2_2_37_1","volume-title":"Proc. Summaries 3rd Annu. JPL Airborne Geosci. Workshop","volume":"1","author":"Yuhas Roberta H","year":"1992","unstructured":"Roberta H Yuhas , Alexander FH Goetz , and Joe W Boardman . 1992 . Discrimination among semi-arid landscape endmembers using the spectral angle mapper (SAM) algorithm . In Proc. Summaries 3rd Annu. JPL Airborne Geosci. Workshop , Vol. 1 . 147--149. Roberta H Yuhas, Alexander FH Goetz, and Joe W Boardman. 1992. Discrimination among semi-arid landscape endmembers using the spectral angle mapper (SAM) algorithm. In Proc. Summaries 3rd Annu. JPL Airborne Geosci. Workshop, Vol. 1. 147--149."},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10590-1_53"},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394171.3413664"},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1080\/014311698215973"},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/2072298.2071932"},{"key":"e_1_3_2_2_42_1","volume-title":"Nima Tajbakhsh, and Jianming Liang.","author":"Zhou Zongwei","year":"2018","unstructured":"Zongwei Zhou , Md Mahfuzur Rahman Siddiquee , Nima Tajbakhsh, and Jianming Liang. 2018 . Unet : A nested u-net architecture for medical image segmentation. In Deep learning in medical image analysis and multimodal learning for clinical decision support. Springer , 3--11. Zongwei Zhou, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh, and Jianming Liang. 2018. Unet: A nested u-net architecture for medical image segmentation. In Deep learning in medical image analysis and multimodal learning for clinical decision support. Springer, 3--11."}],"event":{"name":"MM '21: ACM Multimedia Conference","location":"Virtual Event China","acronym":"MM '21","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 29th ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3474085.3475600","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3474085.3475600","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:48:23Z","timestamp":1750193303000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3474085.3475600"}},"subtitle":["Explicit Spectral-to-Spatial Convolution for Pansharpening"],"short-title":[],"issued":{"date-parts":[[2021,10,17]]},"references-count":42,"alternative-id":["10.1145\/3474085.3475600","10.1145\/3474085"],"URL":"https:\/\/doi.org\/10.1145\/3474085.3475600","relation":{},"subject":[],"published":{"date-parts":[[2021,10,17]]},"assertion":[{"value":"2021-10-17","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}