NVIDIA's new DLSS 4 Super Resolution, which now uses a more complex Transformer model with twice the parameters, was ...

An AI-assisted model developed by researchers from the University of Missouri School of Medicine and the School of ...

On a computer screen, the blurry photo of a flag begins to sharpen. Wrinkles emerge on its surface, creases fluttering in a phantom wind. Zoom in again, and threads begin to appear. Again — and ...

Deep learning-based super-resolution (SR) methods often perform pixel-wise computations uniformly across entire images, even in homogeneous regions where high-resolution refinement is redundant. We ...

Although super-resolution microscopy has produced spectacular images of cellular structures, many of them depict structures that are already well-characterized, creating the mistaken impression ...

Stable Diffusion 3.5 Medium: At 2.5 billion parameters, with improved MMDiT-X architecture and training methods, this model is designed to run "out of the box" on consumer hardware, striking a balance ...

Diffusion models have achieved impressive performance on various image generation tasks, including image super-resolution. Despite their impressive performance, diffusion models suffer from high ...

This repository contains the implementation and pre-trained weights for the paper Exploring the usage of diffusion models for thermal image super-resolution: a generic, uncertainty-aware approach for ...