Geospatial Foundational Embedder: Top-1 Winning Solution on EarthVision Embed2Scale Challenge (CVPR 2025)
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866915484445704192 |
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| author | Xu, Zirui Tang, Raphael Bianco, Mike Zhang, Qi Madhok, Rishi Karianakis, Nikolaos Yu, Fuxun |
| author_facet | Xu, Zirui Tang, Raphael Bianco, Mike Zhang, Qi Madhok, Rishi Karianakis, Nikolaos Yu, Fuxun |
| contents | EarthVision Embed2Scale challenge (CVPR 2025) aims to develop foundational geospatial models to embed SSL4EO-S12 hyperspectral geospatial data cubes into embedding vectors that faciliatetes various downstream tasks, e.g., classification, regression, etc. In this technical report, we introduce our proposed method for the Top-1 winning solution on the Embed2Scale Challenge. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_06993 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Geospatial Foundational Embedder: Top-1 Winning Solution on EarthVision Embed2Scale Challenge (CVPR 2025) Xu, Zirui Tang, Raphael Bianco, Mike Zhang, Qi Madhok, Rishi Karianakis, Nikolaos Yu, Fuxun Computer Vision and Pattern Recognition EarthVision Embed2Scale challenge (CVPR 2025) aims to develop foundational geospatial models to embed SSL4EO-S12 hyperspectral geospatial data cubes into embedding vectors that faciliatetes various downstream tasks, e.g., classification, regression, etc. In this technical report, we introduce our proposed method for the Top-1 winning solution on the Embed2Scale Challenge. |
| title | Geospatial Foundational Embedder: Top-1 Winning Solution on EarthVision Embed2Scale Challenge (CVPR 2025) |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2509.06993 |