Generate Images from Lines Generator interijernog dizajna – dizajner Junming Chen

Dizajn Generate Images from Lines Generator interijernog dizajna čiji je autor Junming Chen iznimno je cijenjeni dobitnik prestižne nagrade 2023 Željezna nagrada A' Design Award u natjecateljskoj kategoriji Generativni, Algoritamski, Parametarski i AI-potpomognuti Dizajn.

ŽeljezoGenerativni· 2023

Generate Images from Lines Generator interijernog dizajna

autor/ica Junming Chen

Klijent: Junming Chen

Dobitnik nagrade Željezna nagrada A' Design Award u kategoriji Generativni

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Dizajn

O dizajnu Generate Images from Lines Generator interijernog dizajna

Generiranje slika iz linija je sustav umjetne inteligencije koji stvara prikaze interijernog dizajna iz crteža linija. Sustav se temelji na poboljšanom difuzijskom modelu, treniranom na više od 20.000 slika interijernog dizajna koje su prikupili i označili profesionalni dizajneri. Dizajneri unose ručno nacrtanu ili digitalnu skicu linija te odabiru dekorativni stil, poput modernog, japanskog, europskog ili kineskog. Prikaz se generira u nekoliko sekundi. Dizajni se mijenjaju uređivanjem skice linija, pa nije potrebno ručno modeliranje niti ponovno renderiranje.

Priznanje

O nagradi Željezna nagrada A' Design Award

Generate Images from Lines Generator interijernog dizajna je pobjednik Željezne nagrade A' Design Award, prestižnog priznanja koje se dodjeljuje dobrim dizajnima što ispunjavaju profesionalne i industrijske zahtjeve očekivane od dobro dizajniranih kreacija. Željezni pobjednici pokazuju veliku vještinu, visoku specijalizaciju, stručno razumijevanje i kreativne kapacitete svojih stvaratelja. Očekuje se da Generate Images from Lines Generator interijernog dizajna bude visoko cijenjena, voljena i njegovana kreacija koja je praktična i inovativna. Ovaj dizajn koji je osvojio Željeznu nagradu A' Design Award integrira najbolje industrijske prakse i ima kompetentne tehničke karakteristike povezane sa znanjem i talentom. Generate Images from Lines Generator interijernog dizajna se poštuje zbog svoje temeljitosti i dizajniran je da pruži poboljšanja kvalitete života koja pomažu da svijet postane bolje mjesto.

Iza dizajna

Komplet za medije

Zasluge, članovi tima i tehnički detalji koje je dostavio dizajner.

Jedinstvena svojstva: 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.
Dimenzije i pakiranje: 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.
Oznake: Artificial intelligence, Human-machine collaboration, Interior design, Generative design, Efficient design, Rapid modification, Controllable design, Decoration style control
Proizvodna tehnologija: 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.
Dizajnerski izazov: 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.
Istraživanje: 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.
Inspiracija: 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.
Trajanje projekta: The project is located in Guangzhou, Guangdong Province, China, and was designed in 2023.
Tijek rada: 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.