DeepFloyd

DeepFloyd IF, developed by Stability AI in partnership with its AI research lab DeepFloyd, is a state-of-the-art text-to-image model that showcases advanced capabilities in generating high-quality images from text inputs. This tool represents a significant stride in the field of AI-driven art and image generation.

Key Features of DeepFloyd IF

Advanced Photorealism

DeepFloyd IF's capability to produce images with a high degree of photorealism is one of its standout features. This is quantified by its zero-shot FID score of 6.66 on the COCO dataset, a metric that assesses the performance of text-to-image models, where lower scores denote better performance.

Flexibility in Aspect Ratios

The model showcases versatility in generating images in various aspect ratios, such as vertical, horizontal, and the standard square. This flexibility allows for a broad range of output designs, catering to diverse requirements.

Zero-Shot Image-to-Image Translation

A unique aspect of DeepFloyd IF is its ability to perform zero-shot image-to-image translations. This process involves resizing the original image, applying noise, and then using a new prompt for backward diffusion to denoise and modify the image. This technique allows for the alteration of style, patterns, and details while maintaining the primary form of the source image.

Technical Framework

Modular, Cascaded, Pixel Diffusion Approach

DeepFloyd IF operates on a sophisticated framework comprising modular, cascaded, and pixel diffusion techniques. This structured approach begins with a base model that generates a 64x64 pixel image from a given text prompt. The image then undergoes a two-stage upscaling process through super-resolution models, enhancing the resolution first to 256x256 pixels and finally to 1024x1024 pixels.

Integration of T5-XXL-1.1 Language Model

At the core of DeepFloyd IF's functionality is the T5-XXL-1.1 language model, which serves as a text encoder. This inclusion ensures a profound understanding of text prompts, enabling the model to align them accurately with the generated images.

Training and Dataset

Custom LAION-A Dataset

DeepFloyd IF was trained on the LAION-A dataset, an aesthetic subset of the LAION-5B dataset containing 1 billion image-text pairs. This dataset, specifically curated for training this model, excludes inappropriate content, ensuring the generation of quality outputs.

Licensing and Future Plans

DeepFloyd IF is initially released under a research license, with plans for an open-source release in the future. This aligns with Stability AI's vision of democratizing access to cutting-edge AI technologies.