Categories: AI/ML News

Chain-of-Zoom framework enables extreme super-resolution zoom without retraining

A trio of AI researchers at KAIST AI, in Korea, has developed what they call a Chain-of-Zoom framework that allows the generation of extreme super-resolution imagery using existing super-resolution models without the need for retraining.
AI Generated Robotic Content

Share
Published by
AI Generated Robotic Content

Recent Posts

Flux Kontext is great changing titles

Flux Kontext can change a poster title/text while keeping the font and style. It's really…

5 hours ago

Linear Layers and Activation Functions in Transformer Models

This post is divided into three parts; they are: • Why Linear Layers and Activations…

5 hours ago

LayerNorm and RMS Norm in Transformer Models

This post is divided into five parts; they are: • Why Normalization is Needed in…

5 hours ago

From R&D to Real-World Impact

Palantir’s Advice for the White House OSTP’s AI R&D PlanEditor’s Note: This blog post highlights Palantir’s…

5 hours ago

Build and deploy AI inference workflows with new enhancements to the Amazon SageMaker Python SDK

Amazon SageMaker Inference has been a popular tool for deploying advanced machine learning (ML) and…

5 hours ago

How to build Web3 AI agents with Google Cloud

For over two decades, Google has been a pioneer in AI, conducting groundwork that has…

5 hours ago