OP4KSR enables efficient one-step 4K super-resolution without patches by adapting Flux with RoPE rescaling and periodicity loss to suppress artifacts.
arXiv preprint arXiv:2510.03012 (2025) GramSR: Visual Feature Conditioning for Diffusion-Based Super-Resolution 15
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GramSR uses DINOv3 visual features instead of text captions to condition a one-step diffusion model for super-resolution via sequential pixel, semantic, and texture LoRA modules.
TOC-SR builds a compact one-step diffusion model for image super-resolution achieving 6.6x fewer parameters and 2.8x fewer GMACs while maintaining strong reconstruction quality.
citing papers explorer
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OP4KSR: One-Step Patch-Free 4K Super-Resolution with Periodic Artifact Suppression
OP4KSR enables efficient one-step 4K super-resolution without patches by adapting Flux with RoPE rescaling and periodicity loss to suppress artifacts.
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GramSR: Visual Feature Conditioning for Diffusion-Based Super-Resolution
GramSR uses DINOv3 visual features instead of text captions to condition a one-step diffusion model for super-resolution via sequential pixel, semantic, and texture LoRA modules.
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TOC-SR: Task-Optimal Compact diffusion for Image Super Resolution
TOC-SR builds a compact one-step diffusion model for image super-resolution achieving 6.6x fewer parameters and 2.8x fewer GMACs while maintaining strong reconstruction quality.