Press Release
Generate Images from Lines Ai Interior Design by Junming Chen Receives the A' Design Award in Generative, Algorithmic, Parametric and AI-Assisted Design
The international grand jury of the 2022 - 2023 A' Design Award & Competition recognizes Junming Chen for generative, algorithmic, parametric and ai-assisted design
FOR IMMEDIATE RELEASE
COMO, Italy, April 20, 2023 /DesignNewswire/ A' Design Award & Competition has confirmed the A' Design Award in the Generative, Algorithmic, Parametric and AI-Assisted Design category for Generate Images from Lines Ai Interior Design by Junming Chen. The result belongs to the 2022 - 2023 A' Design Award & Competition and was determined through blind peer review by an international grand jury panel of established academics, design professionals and press members, who scored anonymized entries against predetermined criteria.
About the A' Design Award
The Iron A' Design Award is awarded to good designs that meet the rigorous professional and industrial standards set by the A' Design Awards. This recognition is reserved for works that demonstrate a solid understanding of design principles and show creativity within their execution. Recipients of the Iron A' Design Award are acknowledged for their practical innovations and contributions to their respective fields, providing solutions that improve quality of life and foster positive change. These designs are a testament to the skill and dedication of their creators, showcasing their ability to address real-world challenges through thoughtful design.
More About Generate Images from Lines Ai Interior Design
Generate Images from Lines is an artificial intelligence system that creates interior design renderings from line drawings. The system is based on an improved diffusion model, trained on more than 20,000 interior design images collected and annotated by professional designers. Designers input a hand-drawn or digital line draft and select a decorative style, such as modern, Japanese, European or Chinese. A rendering is produced in a few seconds. Designs are changed by editing the line draft, so manual modeling and re-rendering are not required.
About Junming Chen
Junming Chen is a designer and programmer with a multidisciplinary background. He holds a BA in Architecture, an MS in Design, and an MS in Computing. Currently studying for a doctorate in digital media at Macau University of Science and Technology, and working in the Digital Construction Laboratory of Macau University of Science and Technology. Good at using parametric and artificial intelligence technology for design practice. He designed and built several parametric projects. He has also won many design awards and computer awards.
Award Record
Junming Chen is a winner of 2 A' Design Awards, including this recognition. All of the awards belong to the 2022 - 2023 edition of the A' Design Award & Competition.
About the A' Generative, Algorithmic, Parametric and AI-Assisted Design Award
The A' Generative Design Award is an international design competition recognizing good generative designs from leading creators and designers worldwide. The competition is organized within the A' Design Award & Competition and is open to generative designers, algorithmic design professionals, ai-assisted design experts and parametric designers from all countries. Entries typically include algorithmic artworks, parametric architectures, generative graphics, ai-assisted illustrations, computational sculptures and procedural patterns. Awarded generative designs are published at https://designers.org/design-category/generative
About A' Design Award & Competition
A' Design Award & Competition is an international, juried design accolade organized annually since 2008. The competition is open to entries from all countries. The A' Design Award has a philanthropic mission to advance society through good design by recognizing and promoting superior products, projects and services that benefit society, and by creating a global awareness and appreciation for good design practices and principles. Entries are peer reviewed and anonymously evaluated by an international grand jury panel of established academics, design professionals and press members against predetermined criteria such as functionality, ergonomics, engineering, presentation, innovation, usability, sustainability and technology, with score normalization applied to remove biases. Awards are conferred at Platinum, Gold, Silver, Bronze and Iron levels. The A' Design Prize granted to eligible laureates includes the award trophy, the certificate of design excellence, the hardcover yearbook, a lifetime license to use the A' Design Award winner logo, exhibition of awarded works, an invitation to the gala night and award ceremony in Italy, inclusion in the World Design Rankings and Designer Rankings, and public relations and publicity services. Registration, the upload of a work and the preliminary score are free of charge, and Professional and Digital Edition laureates are not contractually obliged to pay further fees to claim the A' Design Prize. Further information is available at https://competition.adesignaward.com
Press Resources
- Winner Page: https://designers.org/150690
- A' Design Award Page: https://competition.adesignaward.com/150690
- Media Showcase: https://www.designnewsroom.com/!150690
- Laureate Profile: https://designers.org/d/344009
Media Contact
Giulia Ferrari, Press Office
Designers.Org
Via Leone Leoni 32, 22100 Como, Italy
press@designers.org
+39 031 4491953
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Fact Sheet
The Work
- Project
- Generate Images from Lines Ai Interior Design
- Function
- Ai Interior Design
- Category
- Generative, Algorithmic, Parametric and AI-Assisted Design
- Discipline
- Design Strategy
- Industry
- Innovation and Design Industry
- Colors
- Light Gray, Tan, Sienna, Rosy Brown and Gray
- Images
- 5
The Recognition
- Laureate
- Junming Chen
- Country
- China
- Recognition
- A' Design Award
- Edition
- 2022 - 2023
- Design ID
- #150690
Design Details
- Unique Properties
- The design was done by artificial intelligence (AI) in collaboration with designers. We trained an AI that professionally generates interior designs, which can generate interior designs with different decorative styles based on input line drafts. It solves the problem that the traditional design modification requires remodeling and rendering. It only takes a few seconds to generate a design using this method, and the efficiency of generation and modification is increased by dozens of times.
- Inspiration
- The traditional process of obtaining renderings for interior design is tedious and time-consuming. We use artificial intelligence (AI) to generate interior design, improve design efficiency, and explore new ways of human-computer collaborative design. Specifically, we trained an AI to create interior designs, which can quickly generate and modify designs in cooperation with humans. Changing the design does not require modifying the model and re-rendering, which improves design efficiency.
- Research
- Research Background: The interior design process could be more convenient, and the efficiency of design and modification could be higher. Methods: We trained an AI for professional interior design and used AI to cooperate with people to generate interior designs of various decorative styles from line drawings. Results: Using our AI, designers can obtain an interior design rendering every few seconds, efficiently generating and modifying designs. Insights: Our method can quickly generate large batches of interior designs with specified decoration styles and spatial attributes, and the generated results can be changed by modifying the line draft.
- 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, we 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.
- Realization and Technology
- The AI technology we use is our improved diffusion model technology. The typical defect of the diffusion model is that it cannot generate design according to specific "decorative style" and "space attribute," which is fatal for interior design. To this end, we re-collected and manufactured a data set containing more than 20,000 interior design renderings and data annotations and handed the data set to AI learning to generate an AI suitable for interior design. The AI can generate interior renderings specifying "decorative style" and "space attributes" by inputting line sketches.
- Operation and Interaction
- 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 hand-drawn or design line draft into AI to specify the decoration style. 5. AI generates the interior design of the specified decoration style. 6. The designer adjusts the line draft of the unsatisfactory part of the design and then regenerates the design. 7. After adjusting the line draft and generating it multiple times, a good design is obtained.
- Project Duration and Location
- The project is located in Guangzhou, Guangdong Province, China, and was designed in 2023.
- Specifications
- Use artificial intelligence to cooperate with designers to generate designs with different decorative styles. The design area is 160 square meters, and the decoration styles include modern, Japanese, European, and Chinese styles.
- Keywords
- Artificial intelligence, Human-machine collaboration, Interior design, Generative design, Efficient design, Rapid modification, Controllable design, Decoration style control
