Summary of Swiftbrush V2: Make Your One-step Diffusion Model Better Than Its Teacher, by Trung Dao et al.
SwiftBrush v2: Make Your One-step Diffusion Model Better Than Its Teacher
by Trung Dao, Thuan Hoang Nguyen, Thanh Le, Duc Vu, Khoi Nguyen, Cuong Pham, Anh Tran
First submitted to arxiv on: 26 Aug 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 The paper proposes enhancements to the SwiftBrush text-to-image diffusion model, aiming to match its performance with the more complex Stable Diffusion counterpart. The authors initially explore the quality-diversity trade-off between SwiftBrush and SD Turbo, observing that SwiftBrush excels in image diversity while SD Turbo performs better in terms of image quality. To address this, they modify the training methodology by introducing better weight initialization and efficient LoRA training, as well as a novel clamped CLIP loss to improve image-text alignment and quality. The proposed modifications achieve a new state-of-the-art one-step diffusion model, outperforming GAN-based and multi-step Stable Diffusion models with an FID of 8.14. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper makes SwiftBrush, a text-to-image diffusion model, better by changing how it’s trained. It compares SwiftBrush to another similar model called SD Turbo and finds that SwiftBrush is good at making diverse images, but not as good at making high-quality ones. To fix this, the authors try different training methods and add a new way to make the images look like they were described in the text. This makes SwiftBrush even better, beating other models at doing one-step text-to-image generation. |
Keywords
» Artificial intelligence » Alignment » Diffusion » Diffusion model » Gan » Image generation » Lora
