Generate Images from Lines Panasiah Desain Interior dek Junming Chen

Generate Images from Lines Panasiah Desain Interior dek Junming Chen adolah pamenang nan sangaik tahormat dari A' Design Award Basi 2023 nan sangaik prestigius dalam Kategori Kompetisi Generatif.

BasiGeneratif· 2023

Generate Images from Lines Panasiah Desain Interior

dek Junming Chen

Klien: Junming Chen

Pamenang A' Design Award Basi dalam Kategori Generatif

48,097

Pamenang Pangharogaan Taverifikasi

Verifikasi Status Pangharogaan untuak #150690

Caliak di A' Design Award Siaran Pers Lencana Penghargaan

Warno

Desain

Tantang Generate Images from Lines Panasiah Desain Interior

Generate Images from Lines adolah sistem kacadasan buatan nan mancipteknan gambar rendering desain interior dari gambar garih. Sistem iko didasari dek model difusi nan alah disampurnokan, dilatiah jo labiah dari 20.000 gambar desain interior nan dikumpuaknan sarato diberi anotasi dek desainer profesional. Desainer manginpuik draf garih nan dibuek jo tangan atau sacaro digital, sarato mamiliah gaya dekoratif, saroman gaya modern, Jepang, Eropah, atau Cino. Sabuah gambar rendering ka dihasilkan dalam babarapo detik sajo. Parubahan desain dilakukan jo maedit draf garih tu, sahinggo pambuatan model manual sarato rendering baulang indak diparalukan lai.

Pangakuan

Tantang A' Design Award Basi

Generate Images from Lines Panasiah Desain Interior adolah pamenang A' Design Award Basi, sabuah pangakuan nan bapresti nan dibarikan ka rancangan nan elok nan mamanuhi kaparluan profesional jo industri nan dipaokan dari ciptaan nan dirancang jo elok. Pamenang Basi mamparlihatkan kamahiran nan gadang, spesialisasi nan tinggi, pamahaman pakar jo kapasitas kreatif panciptanyo. Generate Images from Lines Panasiah Desain Interior dipaokan manjadi ciptaan nan sangaik dihormati, dikagumi jo disayangi, nan praktis jo inovatif. Rancangan nan manang Basi iko mamasukkan praktik tabaik industri jo punyo ciri teknis nan cakap nan bapautan jo ilimu jo bakaik. Generate Images from Lines Panasiah Desain Interior dihormati karano katalitiannyo jo dirancang untuak maningkekkan kualitas hiduik jo mambantu manjadikan dunia tampek nan labiah elok.

Di Baliak Desain

Kit Pers

Kredit, anggota tim jo rincian teknis nan disadioan dek perancang.

Sifat 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 & Kemasan: 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 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.
Penelitian: 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 Proyek: The project is located in Guangzhou, Guangdong Province, China, and was designed in 2023.
Alua 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.