Summary of Latent Schrodinger Bridge: Prompting Latent Diffusion For Fast Unpaired Image-to-image Translation, by Jeongsol Kim and Beomsu Kim and Jong Chul Ye
Latent Schrodinger Bridge: Prompting Latent Diffusion for Fast Unpaired Image-to-Image Translation
by Jeongsol Kim, Beomsu Kim, Jong Chul Ye
First submitted to arxiv on: 22 Nov 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
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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 Medium Difficulty summary: This paper introduces Schrodinger Bridges (SBs), stochastic differential equations that enable minimal transport cost between distributions. Building upon the concept of diffusion models, SBs decompose their vector field into source, target, and noise predictors. The authors propose Latent Schrodinger Bridges (LSBs) that approximate the SB ODE via pre-trained Stable Diffusion and develop prompt optimization and change of variables formula for efficient training and inference. LSBs demonstrate competitive image-to-image translation performance in unsupervised settings with significantly reduced computational cost compared to previous diffusion model-based methods. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Low Difficulty summary: This research paper is about a new way to translate images from one style to another without needing any examples or labels. The old method, called diffusion models, can be slow and uses a lot of computer power. The new method, called Schrodinger Bridges, is faster and more efficient. It works by breaking down the image into smaller pieces and matching them up between the two styles. The authors tested this new method and found that it works well and is much quicker than the old way. |
Keywords
* Artificial intelligence * Diffusion * Diffusion model * Inference * Optimization * Prompt * Translation * Unsupervised
