Image Super-Resolution Models

PULSE is a self-supervised photo upsampling algorithm. Instead of starting with the LR image and slowly adding detail, PULSE traverses the high-resolution natural image manifold, searching for images that downscale to the original LR image. This is formalized through the downscaling loss, which guides exploration through the latent space of a generative model. By leveraging properties of high-dimensional Gaussians, the authors aim to restrict the search space to guarantee realistic outputs.

Source: PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models

Papers


Paper Code Results Date Stars

Tasks


Task Papers Share
Super-Resolution 2 28.57%
Heart rate estimation 1 14.29%
Photoplethysmography (PPG) 1 14.29%
Denoising 1 14.29%
Face Hallucination 1 14.29%
Image Super-Resolution 1 14.29%

Components


Component Type
🤖 No Components Found You can add them if they exist; e.g. Mask R-CNN uses RoIAlign

Categories