Generate Images from Lines Générator Desain Interior ku Junming Chen

Karya Generate Images from Lines Générator Desain Interior ku Junming Chen nyaéta pamenang anu dihormat pisan tina 2023 A' Design Award Beusi anu bergengsi dina Katégori Kompetisi Géneratif.

BeusiGéneratif· 2023

Generate Images from Lines Générator Desain Interior

ku Junming Chen

Klién: Junming Chen

Pamenang A' Design Award Beusi dina Katégori Géneratif

48,097

Pamenang Panghargaan anu Diverifikasi

Verifikasi Status Panghargaan pikeun #150690

Tingali di A' Design Award Siaran Pers Lencana Panghargaan

Warna

Désain

Ngeunaan Generate Images from Lines Générator Desain Interior

Generate Images from Lines nyaéta sistem kecerdasan buatan anu ngahasilkeun rendering desain interior tina gambar garis. Sistem ieu dumasar kana model difusi anu geus dironjatkeun, dilatih ku leuwih ti 20.000 gambar desain interior anu dikumpulkeun sarta dianotasi ku desainer profésional. Desainer input draf garis anu digambar ku leungeun atawa digital sarta milih gaya dékoratif, saperti modern, Jepang, Éropa, atawa Cina. Rendering dihasilkeun dina sababaraha detik. Desain dirobah ku cara ngédit draf garisna, ku kituna teu perlu modeling manual jeung ngarender deui.

Pangakuan

Ngeunaan A' Design Award Beusi

Generate Images from Lines Générator Desain Interior mangrupa juara A' Design Award Beusi, pangakuan anu bergengsi anu dipasihkeun ka desain alus anu minuhan sarat profésional jeung industri anu diharepkeun tina kréasi anu dirarancang alus. Para juara Beusi nunjukkeun kaahlian anu hébat, spésialisasi anu luhur, pamahaman ahli jeung kamampuh kréatif para kréatorna. Generate Images from Lines Générator Desain Interior diharepkeun jadi kréasi anu dihargaan, dikagumi jeung dipikanyaah anu praktis jeung inovatif. Desain juara A' Design Award Beusi ieu ngalebetkeun prakték pangalusna industri sarta ngabogaan ciri téknis anu mampuh pakait jeung pangweruh praktis jeung bakat. Generate Images from Lines Générator Desain Interior dihormat pikeun katelitianana sarta dirarancang pikeun méré paningkatan kualitas hirup anu mantuan ngajadikeun dunya tempat nu leuwih hadé.

Di Balik Désain

Kit Pers

Krédit, anggota tim sareng detil téknis anu disayogikeun ku désainer.

Sipat 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.
Diménsi & Bungkusan: 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
Téknologi Produksi: 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.
Tantangan Desain: 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.
Panalungtikan: 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.
Durasi Proyék: The project is located in Guangzhou, Guangdong Province, China, and was designed in 2023.
Alur 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.