TexADiff integrates a Relative Texture Density Map into diffusion-based super-resolution to address imbalanced textures in remote sensing images, yielding better high-frequency details and downstream task gains.
Scaling up to excellence: Practicing model scaling for photo- realistic image restoration in the wild
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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The NTIRE 2026 real-world face restoration challenge report details outcomes from 9 valid team submissions advancing perceptual quality and identity consistency in degraded face images.
citing papers explorer
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Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework
TexADiff integrates a Relative Texture Density Map into diffusion-based super-resolution to address imbalanced textures in remote sensing images, yielding better high-frequency details and downstream task gains.
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The Second Challenge on Real-World Face Restoration at NTIRE 2026: Methods and Results
The NTIRE 2026 real-world face restoration challenge report details outcomes from 9 valid team submissions advancing perceptual quality and identity consistency in degraded face images.