Diffusion Models for Earth Observation Use-cases: from cloud removal to urban change detection
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866909111288856576 |
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| author | Sanguigni, Fulvio Czerkawski, Mikolaj Papa, Lorenzo Amerini, Irene Saux, Bertrand Le |
| author_facet | Sanguigni, Fulvio Czerkawski, Mikolaj Papa, Lorenzo Amerini, Irene Saux, Bertrand Le |
| contents | The advancements in the state of the art of generative Artificial Intelligence (AI) brought by diffusion models can be highly beneficial in novel contexts involving Earth observation data. After introducing this new family of generative models, this work proposes and analyses three use cases which demonstrate the potential of diffusion-based approaches for satellite image data. Namely, we tackle cloud removal and inpainting, dataset generation for change-detection tasks, and urban replanning. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2311_06222 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Diffusion Models for Earth Observation Use-cases: from cloud removal to urban change detection Sanguigni, Fulvio Czerkawski, Mikolaj Papa, Lorenzo Amerini, Irene Saux, Bertrand Le Computer Vision and Pattern Recognition The advancements in the state of the art of generative Artificial Intelligence (AI) brought by diffusion models can be highly beneficial in novel contexts involving Earth observation data. After introducing this new family of generative models, this work proposes and analyses three use cases which demonstrate the potential of diffusion-based approaches for satellite image data. Namely, we tackle cloud removal and inpainting, dataset generation for change-detection tasks, and urban replanning. |
| title | Diffusion Models for Earth Observation Use-cases: from cloud removal to urban change detection |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2311.06222 |