Reka bentuk Generate Images from Lines Penjana Reka Bentuk Dalaman oleh Junming Chen ialah pemenang yang sangat dihormati bagi 2023 A' Design Award Besi yang amat berprestij dalam Kategori Pertandingan Reka Bentuk Generatif, Algoritmik, Parametrik dan Berbantu AI.
BesiGeneratif· 2023
Generate Images from Lines Penjana Reka Bentuk Dalaman
oleh Junming Chen
Klien: Junming Chen
Pemenang A' Design Award Besi dalam Kategori Generatif
Pemenang Anugerah Yang Disahkan
Sahkan Status Anugerah untuk #150690Reka Bentuk
Mengenai Generate Images from Lines Penjana Reka Bentuk Dalaman
Generate Images from Lines adalah sistem kecerdasan buatan yang menghasilkan lukisan render reka bentuk dalaman daripada lukisan garisan. Sistem ini berasaskan model resapan (diffusion model) yang dipertingkatkan, dilatih menggunakan lebih daripada 20,000 imej reka bentuk dalaman yang dikumpul dan dianotasi oleh pereka bentuk profesional. Pereka bentuk memasukkan draf garisan lakaran tangan atau digital dan memilih gaya hiasan, seperti moden, Jepun, Eropah atau Cina. Satu render dihasilkan dalam beberapa saat. Reka bentuk boleh diubah dengan menyunting draf garisan, sekaligus menghapuskan keperluan untuk pemodelan manual dan render semula.
Pengiktirafan
Mengenai A' Design Award Besi
Generate Images from Lines Penjana Reka Bentuk Dalaman ialah pemenang A' Design Award Besi, pengiktirafan yang berprestij yang dianugerahkan kepada reka bentuk yang baik yang memenuhi keperluan profesional dan industri yang dijangka daripada ciptaan yang direka dengan baik. Pemenang Besi menunjukkan kemahiran yang besar, kepakaran yang tinggi, kefahaman pakar dan keupayaan kreatif penciptanya. Generate Images from Lines Penjana Reka Bentuk Dalaman diharapkan menjadi ciptaan yang sangat dihargai, dikagumi dan disayangi yang praktikal dan inovatif. Reka bentuk pemenang A' Design Award Besi ini menyepadukan amalan terbaik industri dan mempunyai ciri teknikal yang kompeten yang dikaitkan dengan kepakaran dan bakat. Generate Images from Lines Penjana Reka Bentuk Dalaman dihormati kerana ketelitiannya dan direka untuk memberikan peningkatan kualiti hidup yang membantu menjadikan dunia tempat yang lebih baik.
Di Sebalik Reka Bentuk
Kit Akhbar
Kredit, ahli pasukan dan butiran teknikal yang disediakan oleh pereka.
- Ciri-Ciri Unik
- 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.
- Dimensi & Pembungkusan
- 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.
- Tag
- Artificial intelligence, Human-machine collaboration, Interior design, Generative design, Efficient design, Rapid modification, Controllable design, Decoration style control
- Teknologi Pengeluaran
- 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.
- Cabaran Reka Bentuk
- 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.
- Penyelidikan
- 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. - Inspirasi
- 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.
- Tempoh Projek
- The project is located in Guangzhou, Guangdong Province, China, and was designed in 2023.
- Aliran Operasi
- 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.
Ditaja
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