Summary of Unic-adapter: Unified Image-instruction Adapter with Multi-modal Transformer For Image Generation, by Lunhao Duan et al.
UNIC-Adapter: Unified Image-instruction Adapter with Multi-modal Transformer for Image Generation
by Lunhao Duan, Shanshan Zhao, Wenjun Yan, Yinglun Li, Qing-Guo Chen, Zhao Xu, Weihua Luo, Kaifu Zhang, Mingming Gong, Gui-Song Xia
First submitted to arxiv on: 25 Dec 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 This paper introduces a novel approach to text-to-image generation, addressing the challenge of controlling pixel-level layouts, object appearances, and global styles using text prompts alone. The Unified Image-Instruction Adapter (UNIC-Adapter) is proposed as a single framework that enables flexible and controllable generation across diverse conditions without requiring multiple specialized models. This is achieved by incorporating both conditional images and task instructions into the image generation process through a cross-attention mechanism enhanced by Rotary Position Embedding. Experimental results demonstrate the effectiveness of the UNIC-Adapter in various tasks, including pixel-level spatial control, subject-driven image generation, and style-image-based image synthesis. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Text-to-image generation models have made great progress, but they often struggle to achieve precise control over image layouts, objects, and styles using text prompts alone. To solve this problem, some previous works use conditional images as auxiliary inputs for image generation, which requires specialized models. This paper proposes a new approach that unifies controllable generation within a single framework called the Unified Image-Instruction Adapter (UNIC-Adapter). The UNIC-Adapter is built on the Multi-Modal-Diffusion Transformer architecture and can generate images with flexible and controlled settings. |
Keywords
» Artificial intelligence » Cross attention » Diffusion » Embedding » Image generation » Image synthesis » Multi modal » Transformer
