Only Text Fonction Primària : Aisina de Concepcion Interiora Generativa by Zichun Shao is a highly esteemed winner of the very prestigious 2023 A' Design Award de Fèrre in Generatiu Competition Category.
FèrreGeneratiu· 2023
Only Text Fonction Primària : Aisina de Concepcion Interiora Generativa
by Zichun Shao
Client: Zichun Shao
A' Design Award de Fèrre Winner in Generatiu Category
Verified Award Winner
Verify Award Status for #150725The Design
About Only Text Fonction Primària : Aisina de Concepcion Interiora Generativa
Tèxte del Libre : Only Text es una aisina de concepcion generativa que crea d'imatges de decoracion interiora a partir de descripcions escrichas. L'aisina se basa sus un modèl de difusion format per la concepcion interiora professionala. Mai de 20 000 rendus d'interiors foguèron collectats e etiquetats per de dissenhaires per constituir lo jòc de donadas d'entraïnament. Only Text pòt produire una vista interiora en quauques segondas, amb un estil de decoracion e d'atributs d'espaci causits. Los detalhs se modifican en editant lo tèxte e en tornant generar. Aquesta metòde suprimís la modelizacion e lo rendut manuals, çò que permet de partejar rapidament fòrça opcions amb los clients.
The Recognition
About the A' Design Award de Fèrre
Only Text Fonction Primària : Aisina de Concepcion Interiora Generativa a ganhat la distincion A' Design Award de Fèrre, una reconeissença prestigiosa acordada a de bons designs que respondon a las exigéncias professionalas e industrialas esperadas de creacions plan concebudas. Los ganhaires del Fèrre demòstran una granda abilitat, una nauta especializacion, una comprenedura d'expèrt e la capacitat creativa de lors creators. S'espèra que Only Text Fonction Primària : Aisina de Concepcion Interiora Generativa siá una creacion fòrça considerada, admirada e estimada, practica e innovanta. Aqueste design ganhaire de la distincion A' Design Award de Fèrre integra las melhoras practicas del sector e a de caracteristicas tecnicas competentas ligadas a un saber-far e a un talent. Per son rigor, Only Text Fonction Primària : Aisina de Concepcion Interiora Generativa merita lo respècte e es destinat a aportar de melhoraments a la qualitat de la vida que ajudan a far del mond un luòc melhor.
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.
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