鉄 ジェネラティブ · 2023
Generate Images from Lines インテリアデザインジェネレーター
by Junming Chen
- A' Design Award 鉄賞 2023 in ジェネラティブ
- CLIENT: Junming Chen
- Estimated Number of Design Views: 47,588
- Verification code E1E00EB23C · Verify this award
Colors
About Generate Images from Lines インテリアデザインジェネレーター
「Generate Images from Lines」は、線画からインテリアデザインのレンダリングを生成する人工知能システムである。本システムは改良版の拡散モデルを基盤とし、プロのデザイナーが収集・アノテーションした2万点を超えるインテリアデザイン画像を用いて学習されている。デザイナーは手描きまたはデジタルの線画ドラフトを入力し、モダン、和風、ヨーロピアン、中国風などの装飾スタイルを選択する。数秒でレンダリングが生成される。デザインの変更は線画ドラフトを編集することで行えるため、手作業によるモデリングや再レンダリングは不要である。
About the A' Design Award 鉄賞
Generate Images from Lines インテリアデザインジェネレーターは、よく設計された創造物に期待される専門的・産業的要件を満たす優れたデザインに授与される、権威ある評価である A' Design Award 鉄賞の受賞作品です。鉄賞の受賞作品は、制作者の高い技量、高度な専門性、専門家としての理解、創造的な能力を示しています。Generate Images from Lines インテリアデザインジェネレーターは、高く評価され、称賛され、愛される、実用的で革新的な創造物であることが期待されます。この A' Design Award 鉄賞を受賞したデザインは、業界のベストプラクティスを統合し、ノウハウと才能に結びついた有能な技術的特性を備えています。Generate Images from Lines インテリアデザインジェネレーターは、その徹底ぶりで尊敬され、世界をより良い場所にするための生活の質の向上をもたらすよう設計されています。
Press Kit
- 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.