Generate Images from Lines 室內設計生成器 by Junming Chen

Generate Images from Lines 室內設計生成器 by Junming Chen is a highly esteemed winner of the very prestigious 2023 A' Design Award 鐵獎 in 生成式設計 Competition Category.

鐵生成式· 2023

Generate Images from Lines 室內設計生成器

by Junming Chen

Client: Junming Chen

A' Design Award 鐵獎 Winner in 生成式 Category

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Verified Award Winner

Verify Award Status for #150690

View at A' Design Award Press Release Award Badge

Colors

The Design

About Generate Images from Lines 室內設計生成器

《從線條生成圖像》係一套人工智能系統，可以根據線稿生成室內設計效果圖。呢個系統以改良版嘅擴散模型為基礎，並由專業設計師收集同標註超過二萬張室內設計圖片進行訓練。設計師只需輸入手繪或數碼線稿，並選擇裝飾風格，例如現代風、日式風、歐式風或中式風，短短幾秒之內就可以生成一張效果圖。設計上嘅改動只需修改線稿即可完成，毋須再進行人手建模同重新渲染。

The Recognition

About the A' Design Award 鐵獎

Generate Images from Lines 室內設計生成器是 A' Design Award 鐵獎得主，這是授予滿足人們對設計精良的創作所期待的專業與工業要求的優良設計的聲望認可。鐵獎得主展現出其創作者的高超技藝、高度專業化、專家級的理解力和創造能力。預計Generate Images from Lines 室內設計生成器將成為一件備受推崇、令人欽佩且被珍愛的創作，既實用又創新。這件贏得 A' Design Award 鐵獎的設計整合了行業最佳實踐，並擁有與專業知識和才華相結合的稱職技術特性。Generate Images from Lines 室內設計生成器因其嚴謹而受到尊重，旨在提供有助於讓世界變得更美好的生活品質改善。

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. 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.
Dimensions & Packaging: 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
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.
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 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.