AI RESEARCH
TinySR: Pruning Diffusion for Real-World Image Super-Resolution
arXiv CS.CV
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ArXi:2508.17434v2 Announce Type: replace Real-world image super-resolution (Real-ISR) focuses on recovering high-quality images from low-resolution inputs that suffer from complex degradations like noise, blur, and compression. Recently, diffusion models (DMs) have shown great potential in this area by leveraging strong generative priors to re fine details. However, their iterative denoising process incurs high computational overhead, posing challenges for real-time applications.