SSSGAN: Satellite Style and Structure Generative Adversarial Networks

SSSGAN: Satellite Style and Structure Generative Adversarial Networks

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 s...

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Bibliografiska uppgifter
Huvudupphovsmän: Javier Marín, Sergio Escalera
Materialtyp: Artikel
Språk:English
Publicerad: MDPI AG 2021-10-01
Serie:Remote Sensing
Ämnen:
aerial image generation
satellite image generation
generative adversarial network
deep learning
structure map
style vector
Länkar:https://www.mdpi.com/2072-4292/13/19/3984

Internet

https://www.mdpi.com/2072-4292/13/19/3984

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