Only Text Ferramenta de Deseño de Interiores Xenerativa by Zichun Shao

Only Text Ferramenta de Deseño de Interiores Xenerativa by Zichun Shao is a highly esteemed winner of the very prestigious 2023 A' Design Award de Ferro in Deseño Xerativo, Algorítmico, Paramétrico e Asistido por IA Competition Category.

FerroXerativo· 2023

Only Text Ferramenta de Deseño de Interiores Xenerativa

by Zichun Shao

Client: Zichun Shao

A' Design Award de Ferro Winner in Xerativo Category

43,980
Verified Award Winner
Verify Award Status for #150725

View at A' Design Award Press Release Award Badge

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The Design

About Only Text Ferramenta de Deseño de Interiores Xenerativa

Only Text é unha ferramenta de deseño xenerativo que crea imaxes de deseño de interiores a partir de descricións escritas. A ferramenta baséase nun modelo de difusión adestrado especificamente para o deseño de interiores profesional. Recolléronse e etiquetáronse máis de 20.000 renderizacións de interiores por parte de deseñadores para conformar o conxunto de datos de adestramento. Only Text pode producir unha vista de interior en poucos segundos, cun estilo decorativo e uns atributos espaciais escollidos. Os detalles cámbianse editando o texto e xerando de novo a imaxe. Este método elimina o modelado e a renderización manuais, polo que se poden compartir moitas opcións cos clientes de forma rápida.

The Recognition

About the A' Design Award de Ferro

Only Text Ferramenta de Deseño de Interiores Xenerativa gañou o A' Design Award de Ferro, un recoñecemento prestixioso outorgado a bos deseños que cumpren os requisitos profesionais e industriais esperados de creacións ben deseñadas. Os gañadores Ferro demostran a gran habilidade, a alta especialización, a comprensión experta e a capacidade creativa dos seus creadores. Espérase que Only Text Ferramenta de Deseño de Interiores Xenerativa sexa unha creación moi apreciada, admirada e querida que é práctica e innovadora. Este deseño gañador do A' Design Award de Ferro integra as mellores prácticas do sector e ten características técnicas competentes ligadas ao saber facer e ao talento. Only Text Ferramenta de Deseño de Interiores Xenerativa é respectado pola súa minuciosidade e está deseñado para proporcionar melloras na calidade de vida que axudan a facer do mundo un lugar mellor.

Behind the Design

Press Kit

Credits, team members and technical details provided by the designer.

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.
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.
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.