Junming Chen ᱨᱮᱱᱟᱜ Generate Images from Lines Interior Design Generator (गोर उकिल जनक) ᱫᱚ ᱡᱮᱱᱟᱨᱮᱴᱤᱵ ᱯᱨᱚᱛᱤᱡᱚᱜᱤᱛᱟ ᱵᱷᱟᱜ ᱨᱮ 2023 A' Design Award ᱞᱚᱦᱟ ᱯᱩᱨᱚᱥᱠᱟᱨ ᱨᱮᱱᱟᱜ ᱟᱹᱰᱤ ᱢᱟᱱ ᱟᱠᱟᱱ ᱡᱤᱛᱠᱟᱨ ᱠᱟᱱᱟ᱾
ᱞᱚᱦᱟᱡᱮᱱᱟᱨᱮᱴᱤᱵ· 2023
Generate Images from Lines Interior Design Generator (गोर उकिल जनक)
Junming Chen ᱞᱮᱠᱟᱛᱮ
ᱜᱟᱦᱟᱠ: Junming Chen
ᱡᱮᱱᱟᱨᱮᱴᱤᱵ ᱵᱷᱟᱜ ᱨᱮ A' Design Award ᱞᱚᱦᱟ ᱯᱩᱨᱚᱥᱠᱟᱨ ᱡᱤᱛᱠᱟᱨ
ᱡᱟᱸᱪ ᱟᱠᱟᱱ ᱮᱣᱟᱨᱰ ᱡᱤᱛᱠᱟᱨ
#150690 ᱞᱟᱜᱤᱫ ᱮᱣᱟᱨᱰ ᱦᱟᱞᱚᱛ ᱡᱟᱸᱪᱰᱤᱡᱟᱭᱤᱱ
Generate Images from Lines Interior Design Generator (गोर उकिल जनक) ᱵᱟᱵᱚᱛ ᱛᱮ
Generate Images from Lines बा एकटा कृत्रिम बुद्धि (Artificial Intelligence) व्यवस्था लेखा जाहाँ रेखा चित्र (line drawings) रेयाक़ ते इंटीरियर डिजाइन रेंडरिंग बनाव लागित बानायेनाय आकान। एहोन व्यवस्था बा उन्नत डिफ्यूजन मॉडेल (diffusion model) रेयाक़ बुते बनाया आकान, बाकिन पेशेवर डिजाइनर कहनी जमाओ आर टीका देवाकान 20,000 बेसी इंटीरियर डिजाइन गोर रेयाक़ बुते प्रशिक्षित काना। डिजाइनर कु हाथे आगु काना अथवा डिजिटल रेखा चित्र नामाव आर एकटा सजावट शैली, जेना आधुनिक, जापानी, यूरोपीय अथवा चीनी, बाछाव काना। किछु सेकेंड रे एकटा रेंडरिंग बना काना। रेखा चित्र रे बदल एने डिजाइन कुयाक़ बदल हो जाना, ओना ला हाथेते मॉडलिंग आर फिनु-रेंडरिंग रेयाक़ दरकार बाङ काना।
ᱢᱟᱱᱟᱱ
A' Design Award ᱞᱚᱦᱟ ᱯᱩᱨᱚᱥᱠᱟᱨ ᱵᱟᱵᱚᱛ ᱛᱮ
Generate Images from Lines Interior Design Generator (गोर उकिल जनक) ᱫᱚ A' Design Award ᱞᱚᱦᱟ ᱯᱩᱨᱚᱥᱠᱟᱨ ᱧᱟᱢ ᱟᱠᱟᱱᱟ, ᱱᱚᱶᱟ ᱫᱚ ᱵᱷᱟᱞᱟᱭ ᱰᱤᱡᱟᱭᱤᱱ ᱠᱚ ᱞᱟᱹᱜᱤᱫ ᱮᱢ ᱟᱠᱟᱱ ᱥᱚᱢᱟᱱ ᱠᱟᱱᱟ᱾ ᱱᱚᱶᱟ ᱠᱚ ᱫᱚ ᱰᱤᱡᱟᱭᱤᱱᱟᱨ ᱠᱚ ᱨᱮᱭᱟᱜ ᱵᱷᱟᱵᱱᱟ ᱟᱨ ᱵᱷᱟᱞᱟᱭ ᱠᱟᱢᱤ ᱡᱷᱟᱞᱠᱟᱣ ᱠᱚ᱾ Generate Images from Lines Interior Design Generator (गोर उकिल जनक) ᱫᱚ ᱠᱚᱞᱟ, ᱣᱤᱜᱭᱟᱱ, ᱰᱤᱡᱟᱭᱤᱱ ᱟᱨ ᱴᱮᱠᱱᱚᱞᱚᱡᱤ ᱨᱮᱭᱟᱜ ᱥᱤᱢᱟ ᱵᱟᱲᱦᱟᱣ ᱟᱨ ᱫᱩᱱᱤᱭᱟ ᱵᱷᱟᱞᱟᱭ ᱞᱟᱹᱜᱤᱫ ᱜᱚᱲᱚ ᱮᱢ ᱠᱟᱱᱟ᱾
ᱰᱤᱡᱟᱭᱤᱱ ᱯᱤᱪᱷᱟ ᱨᱮ
ᱯᱨᱮᱥ ᱠᱤᱴ
ᱰᱤᱡᱟᱭᱤᱱᱟᱨ ᱧᱮᱞ ᱠᱷᱚᱱ ᱠᱨᱮᱰᱤᱴ, ᱴᱤᱢ ᱥᱫᱚᱥᱭ ᱟᱨ ᱴᱮᱠᱱᱤᱠᱮᱞ ᱵᱤᱵᱚᱨᱚᱬ ᱮᱢ ᱟᱠᱟᱱᱟ᱾
- ᱟᱞᱜᱟ ᱜᱩᱱ ᱠᱚ
- 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.
- ᱢᱟᱯ ᱟᱨ ᱯᱮᱠᱮᱡᱤᱝ
- 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.
- ᱴᱮᱜ ᱠᱚ
- Artificial intelligence, Human-machine collaboration, Interior design, Generative design, Efficient design, Rapid modification, Controllable design, Decoration style control
- ᱛᱮᱭᱟᱨ ᱛᱮᱠᱱᱚᱞᱚᱡᱤ
- 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.
- ᱰᱤᱡᱟᱭᱱ ᱪᱮᱞᱮᱧ
- 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.
- ᱜᱚᱵᱮᱥᱚᱱᱟ
- 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. - ᱯᱨᱮᱨᱚᱱᱟ
- 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.
- ᱯᱨᱚᱡᱮᱠᱴ ᱥᱚᱢᱚᱭ
- The project is located in Guangzhou, Guangdong Province, China, and was designed in 2023.
- ᱠᱟᱹᱢᱤ ᱦᱚᱨ
- 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.
ᱥᱯᱚᱱᱥᱚᱨᱰ
Designers.org ᱠᱷᱚᱱ ᱯᱟᱨᱚᱢ ᱛᱟᱞᱟᱥ
ᱟᱞᱮᱭᱟᱜ ᱵᱤᱜᱽᱭᱟᱯᱚᱱ ᱥᱟᱹᱜᱟᱹᱭ ᱠᱚ ᱠᱷᱚᱱ ᱯᱨᱚᱰᱟᱠᱴ, ᱥᱮᱵᱟ ᱟᱨ ᱢᱚᱠᱟ ᱩᱫᱩᱜ ᱢᱮ᱾
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ᱥᱟᱹᱜᱟᱹᱭ ᱰᱤᱡᱟᱭᱤᱱ ᱠᱚ
ᱢᱤᱫ ᱞᱮᱠᱟ ᱠᱮᱴᱮᱜᱚᱨᱤ ᱠᱷᱚᱱ ᱟᱨᱦᱚᱸ ᱯᱩᱨᱥᱠᱟᱨ ᱧᱟᱢᱟᱠᱟᱱ ᱰᱤᱡᱟᱭᱤᱱ ᱠᱚ ᱧᱮᱞ ᱢᱮ, ᱡᱚᱜᱭᱟᱛᱟ ᱧᱮᱞ ᱛᱮ ᱵᱟᱪᱷᱟᱣ ᱟᱠᱟᱱᱟ᱾
