The recent growth in the number of satellite images fosters the development of effective deep-learning techniques for Remote Sensing (RS). However, their full potential is untapped due to the lack of large annotated datasets. Such a problem is usually countered by fine-tuning a feature extractor that is previously trained on the ImageNet dataset. Unfortunately, the domain of natural images differs from the RS one, which hinders the final performance. In this work, we propose to learn meaningful representations from satellite imagery, leveraging its high-dimensionality spectral bands to reconstruct the visible colors. We conduct experiments on land cover classification (BigEarthNet) and West Nile Virus detection, showing that colorization is a solid pretext task for training a feature extractor. Furthermore, we qualitatively observe that guesses based on natural images and colorization rely on different parts of the input. This paves the way to an ensemble model that eventually outperforms both the above-mentioned techniques.
The color out of space: learning self-supervised representations for Earth Observation imagery / Vincenzi, Stefano; Porrello, Angelo; Buzzega, Pietro; Cipriano, Marco; Fronte, Pietro; Cuccu, Roberto; Ippoliti, Carla; Conte, Annamaria; Calderara, Simone. - (2020), pp. 3034-3041. ((Intervento presentato al convegno 25th International Conference on Pattern Recognition tenutosi a Milan, Italy nel 10-15 January 2021 [10.1109/ICPR48806.2021.9413112].
Data di pubblicazione: | 2020 | |
Titolo: | The color out of space: learning self-supervised representations for Earth Observation imagery | |
Autore/i: | Vincenzi, Stefano; Porrello, Angelo; Buzzega, Pietro; Cipriano, Marco; Fronte, Pietro; Cuccu, Roberto; Ippoliti, Carla; Conte, Annamaria; Calderara, Simone | |
Autore/i UNIMORE: | ||
Digital Object Identifier (DOI): | http://dx.doi.org/10.1109/ICPR48806.2021.9413112 | |
Codice identificativo Scopus: | 2-s2.0-85106192901 | |
Codice identificativo ISI: | WOS:000678409203020 | |
Nome del convegno: | 25th International Conference on Pattern Recognition | |
Luogo del convegno: | Milan, Italy | |
Data del convegno: | 10-15 January 2021 | |
Serie: | INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION | |
Pagina iniziale: | 3034 | |
Pagina finale: | 3041 | |
Citazione: | The color out of space: learning self-supervised representations for Earth Observation imagery / Vincenzi, Stefano; Porrello, Angelo; Buzzega, Pietro; Cipriano, Marco; Fronte, Pietro; Cuccu, Roberto; Ippoliti, Carla; Conte, Annamaria; Calderara, Simone. - (2020), pp. 3034-3041. ((Intervento presentato al convegno 25th International Conference on Pattern Recognition tenutosi a Milan, Italy nel 10-15 January 2021 [10.1109/ICPR48806.2021.9413112]. | |
Tipologia | Relazione in Atti di Convegno |
File in questo prodotto:
File | Descrizione | Tipologia | |
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the_color_out_main_paper.pdf | Articolo principale | Post-print dell'autore (bozza post referaggio) | Open Access Visualizza/Apri |
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