Summary of Is One Gpu Enough? Pushing Image Generation at Higher-resolutions with Foundation Models, by Athanasios Tragakis et al.
Is One GPU Enough? Pushing Image Generation at Higher-Resolutions with Foundation Models
by Athanasios Tragakis, Marco Aversa, Chaitanya Kaul, Roderick Murray-Smith, Daniele Faccio
First submitted to arxiv on: 11 Jun 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper introduces Pixelsmith, a novel text-to-image generative framework that enables the sampling of high-resolution images on a single GPU without additional computational costs. The framework’s cascading method uses the image generated at lower resolutions as a baseline to sample higher resolutions, while the Slider mechanism fuses overall structure with fine details. By denoising patches rather than the entire latent space, Pixelsmith reduces memory demands and minimizes sampling time and artifacts. Experimental results demonstrate that Pixelsmith achieves higher quality and diversity compared to existing techniques. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Pixelsmith is a new way to make pictures from words. It’s like a super powerful camera that can take huge photos without using too much computer power. The special method it uses allows it to make the pictures at different sizes, which means it can make really big pictures or really small ones, all on one computer. This helps make the pictures look better and faster too. |
Keywords
» Artificial intelligence » Latent space
