Summary of Tage: Trustworthy Attribute Group Editing For Stable Few-shot Image Generation, by Ruicheng Zhang et al.
TAGE: Trustworthy Attribute Group Editing for Stable Few-shot Image Generation
by Ruicheng Zhang, Guoheng Huang, Yejing Huo, Xiaochen Yuan, Zhizhen Zhou, Xuhang Chen, Guo Zhong
First submitted to arxiv on: 23 Oct 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 This paper introduces TAGE, an innovative image generation network that leverages generative adversarial networks (GANs) to manipulate the attributes of new image classes with limited sample availability. The proposed method comprises three modules: Codebook Learning Module (CLM), Code Prediction Module (CPM), and Prompt-driven Semantic Module (PSM). The CPM module learns category-agnostic attribute representations, predicting indices of these vectors within a discrete codebook to facilitate naturalistic image editing. Additionally, the PSM module generates semantic cues that enhance the model’s comprehension of targeted attributes for editing. Experimental results on Animal Faces, Flowers, and VGGFaces datasets demonstrate superior performance and stability compared to few-shot image generation techniques. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper creates a new way to edit images using computer algorithms. They developed a network called TAGE that can take an image and change certain things about it, like making the animal’s ears bigger or the flower more colorful. This is special because usually these kinds of algorithms need a lot of training data to work well, but TAGE only needs a few examples. The researchers tested their method on different types of images and found that it worked really well. |
Keywords
» Artificial intelligence » Few shot » Image generation » Prompt
