Technology Inheritance Orodje za generiranje arhitekturnih zasnov – avtor Junming Chen

Delo Technology Inheritance Orodje za generiranje arhitekturnih zasnov avtorja Junming Chen je izjemno cenjeni dobitnik prestižne nagrade 2023 Železna nagrada A' Design Award v tekmovalni kategoriji Generativno, algoritemsko, parametrično in z UI podprto oblikovanje.

ŽeleznaGenerativno· 2023

Technology Inheritance Orodje za generiranje arhitekturnih zasnov

avtor/ica: Junming Chen

Naročnik: Chen junming

Dobitnik nagrade Železna nagrada A' Design Award v kategoriji Generativno

45,702

Potrjeni dobitnik nagrade

Preverite status nagrade za #150834

Ogled na A' Design Award Sporočilo za javnost Značka nagrade

Barve

Dizajn

O dizajnu Technology Inheritance Orodje za generiranje arhitekturnih zasnov

Tehnološka dediščina je orodje umetne inteligence, ki generira zasnove zunanjosti stavb. Orodje ustvarja videz stavb v različnih arhitekturnih slogih na podlagi besedila, ki ga vnese uporabnik. Vsaka slika je izdelana v nekaj sekundah, zasnovo pa je mogoče spremeniti z urejanjem besedilnega opisa. Sistem je bil zgrajen z zbiranjem in označevanjem tisočev arhitekturnih upodobitev, nato pa je bil obstoječi model za generiranje slik dodatno izpopolnjen z novim naborom podatkov. Cilj je začetnikom pomagati doseči profesionalno raven kakovosti.

Priznanje

O nagradi Železna nagrada A' Design Award

Technology Inheritance Orodje za generiranje arhitekturnih zasnov je prejemnik Železne nagrade A' Design Award, prestižnega priznanja, ki se podeljuje dobrim oblikovanjem, ki izpolnjujejo profesionalne in industrijske zahteve, pričakovane od dobro zasnovanih stvaritev. Prejemniki Železne nagrade kažejo veliko spretnost, visoko specializacijo, strokovno razumevanje in ustvarjalne zmožnosti svojih ustvarjalcev. Od Technology Inheritance Orodje za generiranje arhitekturnih zasnov se pričakuje, da bo visoko cenjena, občudovana in ljubljena stvaritev, ki je praktična in inovativna. To oblikovanje, nagrajeno z Železno nagrado A' Design Award, vključuje najboljše prakse panoge in ima kompetentne tehnične lastnosti, povezane s strokovnim znanjem in talentom. Zaradi svoje temeljitosti si Technology Inheritance Orodje za generiranje arhitekturnih zasnov zasluži spoštovanje in je zasnovan tako, da zagotavlja izboljšave kakovosti življenja, ki pomagajo narediti svet boljši kraj.

V ozadju dizajna

Komplet za medije

Zasluge, člani ekipe in tehnične podrobnosti, ki jih je posredoval oblikovalec.

Edinstvene lastnosti: This project trains an AI that professionally generates the appearance of buildings. The AI can generate buildings of different architectural styles according to the text entered by the user. The AI only takes a few seconds to generate the building's appearance, and users can recreate the design by changing the text description. That is, designers can obtain design concept proposals through AI cooperation and continuously optimize the design.
Dimenzije in embalaža: Generating building exteriors using a fine-tuned stable diffusion technique.
Oznake: Artificial intelligence, Human-computer cooperation, Architectural appearance generation, Text generation design, Quick modification, Architectural style control
Proizvodna tehnologija: The effect of using stable diffusion to produce architectural appearance could be better. The reason is that this mode needs to sufficiently understand the design skills of different designers, resulting in a messy appearance design and low quality. For this, fine-tuning the existing AI is essential. So this project reworked the data set, fine-tuned the critical stable diffusion, and made an AI to generate the specified architectural style to assist the junior designer in the design.
Oblikovalski izziv: The challenge of this design is to build a professional architectural design AI for generating high-quality and stylized designs. This project collected and marked thousands of architectural appearance renderings of dozens of well-known architects, created a data set of architectural appearance, and then handed the data set to AI for fine-tuning learning. This project builds an AI to generate a given building's exterior style.
Raziskave: Research Background: It is difficult for beginners to design high-quality architectural appearances.
Methods: This project trained an AI to professionally generate building exteriors, which can contract with designers to complete architectural exterior designs.
Results: Using the AI trained in this project, the designer can generate an architectural appearance rendering in just a few seconds.
Insights: Using this method, the architectural appearance of a specified style can be generated and modified through text description, and the quality of the generated design is close to that of a professional designer. This method does not require manual modeling and rendering, which improves design efficiency and quality.
Inspiracija: Most people measure the quality of a building by evaluating how it looks. Good architectural exterior design can bring attention and economic benefits. However, the exterior architectural design is complex, and the quality of architectural exteriors designed by excellent designers and beginners varies greatly. This design makes an artificial intelligence (AI) that can expertly generate building exteriors to help beginners achieve designs that approach the quality of master builders.
Trajanje projekta: The project has already been completed in 2023.
Potek delovanja: 1. Professional designers collect and mark, and screen images of outstanding designer building exteriors.
2. Use the filtered data to train an AI that specializes in generating the exterior of a given architectural style.
3. Designers use AI to design.
4. The designer inputs the design text description into the AI to specify the decoration style.
5. AI generates the interior design of the specified decoration style.
6. Modify the unsatisfactory details in the design through text description, and regenerate the design.
7. After adjusting the text description and generating it multiple times, a good design is obtained.