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Danfeng Hong, Bing Zhang, Xuyang Li, Yuxuan Li, Chenyu Li, Jing Tao Yao, Naoto Yokoya, Hao Li, Pedram Ghamisi, Xiuping Jia and 4 more
The foundation model has recently garnered significant attention due to its potential to revolutionize the field of visual representation learning in a self-supervised manner. While most foundation models are tailored to effectively process RGB images for various visual tasks, there is a noticeable gap in research focused on spectral data, which offers valuable information for scene understanding, especially in remote sensing (RS) applications. To fill this gap, we created for the first time a universal RS foundation model, named SpectralGPT, which is purpose-built to handle spectral RS images using a novel 3D generative pretrained transformer (GPT). Compared to existing foundation models, SpectralGPT 1) accommodates input images with varying sizes, resolutions, time series, and regions in a progressive training fashion, enabling full utilization of extensive RS Big Data; 2) leverages 3D token generation for spatial-spectral coupling; 3) captures spectrally sequential patterns via multi-target reconstruction; and 4) trains on one million spectral RS images, yielding models with over 600 million parameters. Our evaluation highlights significant performance improvements with pretrained SpectralGPT models, signifying substantial potential in advancing spectral RS Big Data applications within the field of geoscience across four downstream tasks: single/multi-label scene classification, semantic segmentation, and change detection.
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Hong, D., Zhang, B., Li, X., Li, Y., Li, C., Yao, J. T., Yokoya, N., Li, H., Ghamisi, P., Jia, X., Plaza, A., Gamba, P. E., Benediktsson, J. A., & Chanussot, J. (2024). SpectralGPT: Spectral Remote Sensing Foundation Model. IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(8), 5227–5244. https://doi.org/10.1109/tpami.2024.3362475
Hong, Danfeng, et al. "SpectralGPT: Spectral Remote Sensing Foundation Model." IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 46, no. 8, 2024, pp. 5227–5244, https://doi.org/10.1109/tpami.2024.3362475.
Hong, Danfeng, Bing Zhang, Xuyang Li, Yuxuan Li, Chenyu Li, Jing Tao Yao, Naoto Yokoya, et al. "SpectralGPT: Spectral Remote Sensing Foundation Model." IEEE Transactions on Pattern Analysis and Machine Intelligence 46, no. 8 (2024): 5227–5244. https://doi.org/10.1109/tpami.2024.3362475.
Hong D., Zhang B., Li X. [и др.] SpectralGPT: Spectral Remote Sensing Foundation Model // IEEE Transactions on Pattern Analysis and Machine Intelligence. — 2024. — Vol. 46, № 8. — P. 5227–5244. — URL: https://doi.org/10.1109/tpami.2024.3362475
@article{hong2024spectralgpt,
title = {{SpectralGPT: Spectral Remote Sensing Foundation Model}},
author = {Danfeng Hong and Bing Zhang and Xuyang Li and Yuxuan Li and Chenyu Li and Jing Tao Yao and Naoto Yokoya and Hao Li and Pedram Ghamisi and Xiuping Jia and Antonio Plaza and Paolo E. Gamba and Jón Atli Benediktsson and Jocelyn Chanussot},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
year = {2024},
volume = {46},
number = {8},
pages = {5227--5244},
doi = {10.1109/tpami.2024.3362475},
url = {https://doi.org/10.1109/tpami.2024.3362475}
}TY - JOUR AU - Hong, Danfeng AU - Zhang, Bing AU - Li, Xuyang AU - Li, Yuxuan AU - Li, Chenyu AU - Yao, Jing Tao AU - Yokoya, Naoto AU - Li, Hao AU - Ghamisi, Pedram AU - Jia, Xiuping AU - Plaza, Antonio AU - Gamba, Paolo E. AU - Benediktsson, Jón Atli AU - Chanussot, Jocelyn TI - SpectralGPT: Spectral Remote Sensing Foundation Model JO - IEEE Transactions on Pattern Analysis and Machine Intelligence VL - 46 IS - 8 SP - 5227 EP - 5244 PY - 2024 DA - 2024/04/03 DO - 10.1109/tpami.2024.3362475 UR - https://doi.org/10.1109/tpami.2024.3362475 ER -
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