arxiv preprint - LayoutGPT: Compositional Visual Planning and Generation with Large Language Models

In this episode we discuss LayoutGPT: Compositional Visual Planning and Generation with Large Language Models by Weixi Feng, Wanrong Zhu, Tsu-jui Fu, Varun Jampani, Arjun Akula, Xuehai He, Sugato Basu, Xin Eric Wang, William Yang Wang. The paper introduces LayoutGPT, a method that uses Large Language Models (LLMs) to generate layouts from text instructions. LayoutGPT utilizes a style sheet language to generate plausible layouts in 2D images and 3D indoor scenes, and performs well in converting challenging language concepts into accurate layout arrangements. When combined with an image generation model, LayoutGPT outperforms text-to-image models and achieves performance comparable to human users in designing visually correct layouts. It also shows promise in 3D indoor scene synthesis, showcasing its potential in different visual domains.