ASASR recasts generative SR flow into Sobolev Riemannian geometry via colored noise kernels and a Riesz-based parametric adversary to optimize along plausible structural failure tangents, claiming better spectral consistency than baselines.
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Coloring the Noise: Adversarial Sobolev Alignment for Faithful Image Super Resolution
ASASR recasts generative SR flow into Sobolev Riemannian geometry via colored noise kernels and a Riesz-based parametric adversary to optimize along plausible structural failure tangents, claiming better spectral consistency than baselines.