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Synthetic data, when grounded in vision-language models for evaluation, demonstrably boosts performance in remote sensing tasks like segmentation and captioning, outperforming models trained solely on real-world data.
Forget fully adapting models: a projection-free local alignment preserves the native CLIP geometry, yielding state-of-the-art out-of-distribution detection performance.
TopoMaskV3's 3D mask head leapfrogs prior 2D methods for road topology understanding, proving that dense offset and height predictions can conquer discretization artifacts and geographic overfitting.
