Chain-of-Zoom factorizes extreme super-resolution into an autoregressive sequence of intermediate scales using a reused backbone model plus GRPO-tuned multi-scale VLM prompts.
Deep learning for image super-resolution: A survey.IEEE transactions on pattern analysis and machine intelligence, 43(10):3365–3387
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A self-supervised framework using SURE and equivariant constraints produces super-resolved Sentinel-5P images comparable to supervised baselines without HR references and with physically plausible structures validated against EMIT data.
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Chain-of-Zoom: Extreme Super-Resolution via Scale Autoregression and Preference Alignment
Chain-of-Zoom factorizes extreme super-resolution into an autoregressive sequence of intermediate scales using a reused backbone model plus GRPO-tuned multi-scale VLM prompts.
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Self-Supervised Super-Resolution for Sentinel-5P Hyperspectral Images
A self-supervised framework using SURE and equivariant constraints produces super-resolved Sentinel-5P images comparable to supervised baselines without HR references and with physically plausible structures validated against EMIT data.