Summary of Training-free Consistent Text-to-image Generation, by Yoad Tewel et al.
Training-Free Consistent Text-to-Image Generation
by Yoad Tewel, Omri Kaduri, Rinon Gal, Yoni Kasten, Lior Wolf, Gal Chechik, Yuval Atzmon
First submitted to arxiv on: 5 Feb 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Graphics (cs.GR); Machine Learning (cs.LG)
GrooveSquid.com Paper Summaries
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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 presents a novel approach called ConsiStory that enables consistent generation of images related to specific subjects across various prompts, without the need for lengthy optimization or large-scale pre-training. The method leverages a pretrained text-to-image model and introduces two key components: a subject-driven shared attention block and correspondence-based feature injection. These components promote subject consistency between generated images while allowing for diverse layouts. The paper compares ConsiStory to several baselines and demonstrates state-of-the-art performance on subject consistency and text alignment, without requiring any optimization step. Additionally, ConsiStory can be extended to handle multiple subjects and even enable personalization for common objects. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary ConsiStory is a new way to make pictures based on words. It’s hard to get the same picture every time when you ask the model to make something specific. Some methods try to teach the model new words, or add special rules to help it understand what you want. But these methods take a long time and can’t always make sure the picture matches what you asked for. ConsiStory is different because it uses a special block inside the model that helps keep the pictures related to what you’re asking for. It also lets the pictures have different layouts, so they don’t all look the same. The paper shows that ConsiStory works better than other methods and can even make multiple related pictures without needing any extra training. |
Keywords
* Artificial intelligence * Alignment * Attention * Optimization
