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.
Enhanced deep residual networks for single image super-resolution
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A multi-scale CNN super-resolution model outperforms baseline CNN, attention CNN, and diffusion-based approaches in reconstructing fine-scale features from under-resolved atmospheric flow simulations on standard benchmarks.
citing papers explorer
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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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Enhancing the accuracy of under-resolved numerical simulations of atmospheric flows with super resolution
A multi-scale CNN super-resolution model outperforms baseline CNN, attention CNN, and diffusion-based approaches in reconstructing fine-scale features from under-resolved atmospheric flow simulations on standard benchmarks.