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Few-Shot Image Classification · benchmark dataset · EN

SAT-493M (Maxar 493M satellite imagery pretraining dataset).

SAT-493M is a large-scale pretraining corpus of commercial Maxar satellite imagery used by the DINOv3 project. It contains approximately 493 million RGB, ortho-rectified image chips (tiles) at 512×512 pixels, sampled at ~0.6 meter ground sampling distance. The collection was assembled from Maxar high-resolution optical imagery and was used to pre-train DINOv3 satellite models (e.g., ViT-7B and distilled variants) to produce high-quality dense features for remote-sensing / overhead-vision tasks. The dataset is a proprietary/commercial compilation of Maxar imagery (not published as an open Hugging Face dataset) and is provided to the DINOv3 team under Maxar licensing; access and redistribution are therefore restricted. Primary sources: DINOv3 paper (arXiv:2508.10104) and the DINOv3 repository / model cards which describe models pretrained on “SAT-493M.”

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