Universal Upscaler Pro (CPU Optimized)

This application provides state-of-the-art (SOTA) image upscaling running entirely on CPU, optimized for free-tier cloud environments.

Available Models

Model Scale Best For License
SPAN (NomosUni) x2 Speed & General Use. Extremely fast, parameter-free attention network. Apache 2.0
RealESRGAN x2 Robustness. Excellent at removing JPEG artifacts and noise. BSD 3-Clause
HAT-S x4 Texture Detail. Hybrid Attention Transformer for high-fidelity restoration. MIT

Attributions & Credits

  • Real-ESRGAN: Wang et al., 2021. Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data.
  • SPAN: Zhang et al., 2023. Swift Parameter-free Attention Network for Efficient Super-Resolution.
  • HAT: Chen et al., 2023. Activating Activation Functions for Image Restoration.
  • NomosUni: Custom SPAN training by Phhofm.
Model Architecture
Output Format

CPU: 78.8% | RAM: 80.7% (61.0 GB used)