Summary of Efficient Conditional Diffusion Model with Probability Flow Sampling For Image Super-resolution, by Yutao Yuan et al.
Efficient Conditional Diffusion Model with Probability Flow Sampling for Image Super-resolution
by Yutao Yuan, Chun Yuan
First submitted to arxiv on: 16 Apr 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: 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 The proposed Efficient Conditional Diffusion Model with Probability Flow Sampling (ECDP) tackles the challenges of image super-resolution by learning a distribution of high-resolution images conditioned on low-resolution images. This approach avoids blurry images common in PSNR-oriented methods, but existing diffusion-based methods suffer from high time consumption and suboptimal quality due to issues like color shifting. ECDP addresses these limitations by introducing a continuous-time conditional diffusion model for efficient generation and a hybrid parametrization for improved consistency. Additionally, an image quality loss is introduced as a complement to the score matching loss, further enhancing super-resolution quality while reducing time consumption. The method is evaluated on DIV2K, ImageNet, and CelebA datasets, outperforming existing diffusion-based methods in terms of both quality and efficiency. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary ECDP is a new way to make blurry pictures clear again by learning how different high-quality images look similar to low-quality ones. This helps avoid making the picture too blurry or changing its colors. The old ways of doing this took a long time and didn’t always produce great results. ECDP makes it faster and better! It works by creating a model that can generate many possible high-quality images from one low-quality image, and then chooses the best one based on how good it looks. |
Keywords
» Artificial intelligence » Diffusion » Diffusion model » Probability » Super resolution
