Explore a technical deep dive video examining the research paper that influenced Flux, a leading generative image model that surpassed DALL-E and PIXART. Learn about the fundamentals of Rectified Flow Transformers, diffusion model mechanics, and loss equation analysis. Discover the inner workings of Latent Diffusion Transformers, examine detailed architectural diagrams, and understand the datasets and preprocessing techniques used. Follow along as the presenter breaks down the model's components, from synthetic data generation with improved captions to fine-tuning results, providing a comprehensive understanding of this breakthrough in AI image generation technology.
Inside the Rectified Flow Transformer Model - Understanding Advanced Image Generation
Overview
Syllabus
Intro to Flux
Rectified Flow Transformers
What Do Diffusion Models Do
Understanding the Loss Equation
How Latent Diffusion Transformers Work
Rectified Flow Transformers Architecture
Rectified Flow Transformer Diagram
The Datasets They Used
Improved Captions Synthetic Data
Data Preprocessing
Our Results Fine-Tuning
Taught by
Oxen
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