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title: README
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## IBM and ESA 🌍 Advancing Geospatial AI with TerraMind & MS-CLIP
IBM and the European Space Agency (ESA) Φ-lab introduce TerraMind, the first multimodal, any-to-any generative foundation model for Earth Observation.
TerraMind reaches new SOTA results on downstream tasks and introduces the "Thinking-in-Modalities" approach to handle missing modalities.
The model was pre-trained in partnership with Jülich Supercomputing Centre (Forschungszentrum Jülich) and supported by the FAST-EO project.
### 🎉 TerraMind has been accepted at ICCV 2025
We’re honored to present our work at one of the most prestigious conferences in computer vision. Stay tuned for more details!
### 🤝 Open Source
The FAST-EO partners and ESA Φ-lab are committed to Open Source, sharing knowledge, and driving innovation for the geospatial domain.
### 📚 Papers and Resources
Explore the technical paper detailing TerraMind's architecture and applications in our [paper](https://arxiv.org/abs/2504.11171). Details on MS-CLIP can be found [here](https://arxiv.org/pdf/2503.15969) (accepted at ECML25) and our pre-training dataset TerraMesh is published [here](https://arxiv.org/abs/2504.11172) (CVPR EarthVision 25).
### 🚀 Challenge
Already working with TerraMind? Submit your use case to the [TerraMind Blue-Sky Challenge](https://huggingface.co/spaces/ibm-esa-geospatial/challenge), a bi-monthly award spotlighting the boldest, most imaginative ways using TerraMind.
Explore our models, datasets, and papers, and join our discussions to shape the future of geospatial AI!
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