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Only Text Generative Design by Zichun Shao
Only Text Generative Design by Zichun Shao
Only Text Generative Design by Zichun Shao
Only Text Generative Design by Zichun Shao
Only Text Generative Design by Zichun Shao

Iron Generative, Algorithmic, Parametric and AI-Assisted Design · 2023

Only Text Generative Design

by Zichun Shao

  • A' Design Award 2023 Iron Winner in Generative, Algorithmic, Parametric and AI-Assisted Design
  • Awarded April 15, 2023
  • CLIENT: Zichun Shao
  • Estimated Number of Design Views: 43,812
  • Verification code 3DD17AA8F3 · Verify this award
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About Only Text Generative Design

Only Text is a generative design tool that creates interior design images from written descriptions. The tool is based on a diffusion model trained for professional interior design. More than 20,000 interior renderings were collected and labeled by designers to form the training data set. Only Text can produce an interior view in a few seconds, with a chosen decoration style and space attributes. Details are changed by editing the text and generating again. The method removes manual modeling and rendering, so many options can be shared with clients quickly.

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Unique Properties
The design was done by artificial intelligence (AI) in collaboration with designers. This project has trained an AI for professional interior design generation, which can generate interior designs with different decoration styles according to the input text. It only takes a few seconds for AI to generate a new interior design, and it can quickly generate a large number of designs for communication with users, thereby improving design efficiency.
Dimensions & Packaging
The project uses diffusion model technology, using artificial intelligence to cooperate with designers to generate designs of different decorative styles. We retrained a professional interior design AI to quickly create designs with varying decoration styles.
Tags
Artificial intelligence, Human-computer collaboration, Interior design, Generative design, Text generative design, Efficient design, Rapid modification, Controllable design, Decoration style control
Production Technology
Ordinary AI cannot generate interior design according to specific "decoration style" and "space attributes," which is a fatal flaw for interior design. To this end, this project collected more than 20,000 interior design renderings, labeled them to make a data set and gave the data set to AI for learning, thus creating an AI suitable for interior design. The AI can generate interior renderings specifying "decorative style" and "space attributes" by inputting text.
Design Challenge
The challenge of this design is to build a professional interior design AI that generates designs of high quality and correct decor. To this end, this project asked professional designers to collect and label tens of thousands of interior design images and then handed over the filtered data to AI for training. Make AI understand what is "decorative style," "spatial attributes," and "aesthetic attributes" and generate an interior design with a specified decorative style.
Project Duration
The project is located in Guangzhou, Guangdong Province, China, and was designed in 2023.
Operation Flow
1. Professional designers collect interior design images and mark and screen them.
2. Use the filtered data to train a professional interior design AI.
3. Designers use AI to design.
4. The designer inputs the design text description into the AI to specify the decoration style.
5. AI generates the interior design of the specified decoration style.
6. Modify the unsatisfactory details in the design through text description, and regenerate the design.
7. After adjusting the text description and generating it multiple times, a good design is obtained.
Research
Research Background: Interior design communication is complex, and obtaining designs and communicating with customers quickly is necessary.
Methods: This project trained an AI to generate interior designs professionally and used the AI to collaborate with humans to create interior designs in various decorative styles from the text.
Results: Using the AI trained in this project, designers can generate an interior design rendering in just a few seconds.
Insights: This project approach rapidly generates large batches of interior designs for specified decor styles and spatial properties and allows new designs to be generated by modifying text. This method eliminates the need for manual modeling and rendering, which improves design efficiency.
Inspiration
It is difficult for users to imagine the scheme described by the designer in words. Designers need to turn thinking into design quickly. With the development of artificial intelligence (AI), designers can generate designs directly from text. Specifically, this project trained an AI to create interior design, which can generate interior design only by inputting text, improving communication efficiency between designers and users.

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