{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T09:27:24Z","timestamp":1774949244478,"version":"3.50.1"},"reference-count":34,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2021,10,5]],"date-time":"2021-10-05T00:00:00Z","timestamp":1633392000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European Regional Development Fund and the Spanish Government, Ministerio de Ciencia, Innovaci\u00f3n y Universidades - Agencia Estatal de Investigaci\u00f3n","award":["RTC2019-007434-7"],"award-info":[{"award-number":["RTC2019-007434-7"]}]},{"name":"Spanish project (MINECO\/FEDER, UE) and CERCA Programme\/Generalitat de Catalunya), and by ICREA under the ICREA Academia programme","award":["PID2019- 105093GB-I00"],"award-info":[{"award-number":["PID2019- 105093GB-I00"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This work presents Satellite Style and Structure Generative Adversarial Network (SSGAN), a generative model of high resolution satellite imagery to support image segmentation. Based on spatially adaptive denormalization modules (SPADE) that modulate the activations with respect to segmentation map structure, in addition to global descriptor vectors that capture the semantic information in a vector with respect to Open Street Maps (OSM) classes, this model is able to produce consistent aerial imagery. By decoupling the generation of aerial images into a structure map and a carefully defined style vector, we were able to improve the realism and geodiversity of the synthesis with respect to the state-of-the-art baseline. Therefore, the proposed model allows us to control the generation not only with respect to the desired structure, but also with respect to a geographic area.<\/jats:p>","DOI":"10.3390\/rs13193984","type":"journal-article","created":{"date-parts":[[2021,10,8]],"date-time":"2021-10-08T21:26:20Z","timestamp":1633728380000},"page":"3984","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["SSSGAN: Satellite Style and Structure Generative Adversarial Networks"],"prefix":"10.3390","volume":"13","author":[{"given":"Javier","family":"Mar\u00edn","sequence":"first","affiliation":[{"name":"Satellogic, Carrer de Bail\u00e8n, 3, 1st Floor, 08010 Barcelona, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0617-8873","authenticated-orcid":false,"given":"Sergio","family":"Escalera","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Informatics, Universitat de Barcelona, Gran via de les Corts Catalanes 585, 08007 Barcelona, Spain"},{"name":"Computer Vision Center, Building O, Campus UAB, Bellaterra (Cerdanyola), 08193 Barcelona, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2021,10,5]]},"reference":[{"key":"ref_1","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","volume":"25","author":"Krizhevsky","year":"2012","journal-title":"Adv. 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