Generate Images from Lines

Ai Interior Design for Junming Chen

It is inefficient to obtain renderings for interior design. This project uses designers to cooperate with artificial intelligence (AI) to generate interior design and improve design efficiency. This project trained an AI to generate interior designs, which take in-line drawings and generates the design. This approach changes the way design is done and solves the problem of interior design modifications requiring remodeling and rendering. It only takes a few seconds to generate a design using this method, and the efficiency of generation and change is increased dozens of times.

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Generate Images from Lines by Junming Chen

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Ai Interior Design by Junming Chen

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Junming Chen Generate Images from Lines

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Junming Chen Ai Interior Design

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Junming Chen Designer Portrait Photo

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Generate Images from Lines Ai Interior Design Press Releases

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Generate Images from Lines Ai Interior Design Media Articles

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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.

Tags

Artificial intelligence, Human-machine collaboration, Interior design, Generative design, Efficient design, Rapid modification, Controllable design, Decoration style control

Production 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.

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, 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.

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 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.

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. Design efficiency is improved by eliminating the need for manual modeling and rendering.

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.

Project Overview

Generate Images from Lines Ai Interior Design has been a Iron winner in the Generative, Algorithmic, Parametric and AI-Assisted Design award category in the year 2022 organized by the prestigious A' Design Award & Competition. 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.

Image Credits

For design images and photos please credit Junming Chen.

Iron Recognition

Junming Chen was recognized with the coveted Iron A' Design Award in 2023, a testament to excellence of their work Generate Images from Lines Ai Interior Design.

Junming Chen Press Releases

Explore the world of Junming Chen through our press releases, designed for media members to use freely and enrich your content. Journalists, gain instant access to 3 press releases today.

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Junming Chen Newsroom

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