Search Results for author:
Found 6 papers, 2 papers with code
Does Diffusion Beat GAN in Image Super Resolution?
There is a prevalent opinion in the recent literature that Diffusion-based models outperform GAN-based counterparts on the Image Super Resolution (ISR) problem.
YaART: Yet Another ART Rendering Technology
In the rapidly progressing field of generative models, the development of efficient and high-fidelity text-to-image diffusion systems represents a significant frontier.
QUASAR: QUality and Aesthetics Scoring with Advanced Representations
This paper introduces a new data-driven, non-parametric method for image quality and aesthetics assessment, surpassing existing approaches and requiring no prompt engineering or fine-tuning.
PyTorch Image Quality: Metrics for Image Quality Assessment
Image Quality Assessment (IQA) metrics are widely used to quantitatively estimate the extent of image degradation following some forming, restoring, transforming, or enhancing algorithms.
Towards Ultrafast MRI via Extreme k-Space Undersampling and Superresolution
We went below the MRI acceleration factors (a. k. a., k-space undersampling) reported by all published papers that reference the original fastMRI challenge, and then considered powerful deep learning based image enhancement methods to compensate for the underresolved images.
An Adaptive Intelligence Algorithm for Undersampled Knee MRI Reconstruction
In this work, we present the application of adaptive intelligence to accelerate MR acquisition.
