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Non-Lambertian scenes can now be accurately decomposed into reflectance and photometric components without auxiliary inputs, revolutionizing hyperspectral imaging analysis.
The study reveals that energy distribution across frequency planes can create unexpected consensus dynamics, defying traditional assumptions in self-attention models.
