Summary of Cityx: Controllable Procedural Content Generation For Unbounded 3d Cities, by Shougao Zhang et al.
CityX: Controllable Procedural Content Generation for Unbounded 3D Cities
by Shougao Zhang, Mengqi Zhou, Yuxi Wang, Chuanchen Luo, Rongyu Wang, Yiwei Li, Zhaoxiang Zhang, Junran Peng
First submitted to arxiv on: 24 Jul 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| 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 a procedural content generation (PCG) technique, named CityX, to create high-fidelity, diverse, and controllable 3D urban scenes. This is achieved by developing a multi-agent framework that transforms multi-modal instructions into executable programs. The method assembles superior assets according to empirical rules, resulting in industrial-grade outcomes. The authors design a management protocol to accommodate extensive PCG plugins with distinct functions and interfaces. CityX demonstrates its superiority in creating realistic 3D urban scenes, which can be used as real-time simulators or infinite data generators for embodied intelligence research. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about creating virtual cities that are very realistic and detailed. This is important because it helps us train and test robots and self-driving cars to make sure they work properly in real-world situations. The authors use a special technique called procedural content generation to create these virtual cities. They developed a system that can take different types of instructions, like maps or images, and turn them into executable programs that can be used to build the city. This allows for a lot of customization and control over what is created. The end result is very realistic and detailed 3D urban scenes that can be used to test robots and self-driving cars. |
Keywords
» Artificial intelligence » Multi modal
