Generate Images from Lines Ai Interior Design by Junming Chen |
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| DESIGN NAME: Generate Images from Lines PRIMARY FUNCTION: Ai Interior Design 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. UNIQUE PROPERTIES / PROJECT DESCRIPTION: 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. OPERATION / FLOW / 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. FITS BEST INTO CATEGORY: Computer Graphics, 3D Modeling, Texturing, and Rendering Design |
PRODUCTION / REALIZATION 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. SPECIFICATIONS / TECHNICAL PROPERTIES: 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. TAGS: Artificial intelligence, Human-machine collaboration, Interior design, Generative design, Efficient design, Rapid modification, Controllable design, Decoration style control RESEARCH ABSTRACT: 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. Design efficiency is improved by eliminating the need for manual modeling and rendering. 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. ADDED DATE: 2023-03-12 10:20:41 TEAM MEMBERS (1) : IMAGE CREDITS: Junming Chen, 2022. |
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NAME: Junming Chen PROFILE: 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. |
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Generate Images From Lines Ai Interior Design by Junming Chen is Winner in Generative, Algorithmic, Parametric and AI-Assisted Design Category, 2022 - 2023.· Press Members: Login or Register to request an exclusive interview with Junming Chen. · Click here to register inorder to view the profile and other works by Junming Chen. |
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