Technology Inheritance Chinangwa Chikuru: Chishandiso Chekugadzira Zvivakwa Zvemazana naJunming Chen

Dhizaini Technology Inheritance Chinangwa Chikuru: Chishandiso Chekugadzira Zvivakwa Zvemazana naJunming Chen ndiye mukundi anokudzwa zvikuru wemubairo unoremekedza we2023 Mubairo weSimbi we A' Design Award muChikwata cheKukwikwidza cheJeneretivu, Argorizimu, Parametriki neInobatsirwa neAI.

SimbiJeneretivu· 2023

Technology Inheritance Chinangwa Chikuru: Chishandiso Chekugadzira Zvivakwa Zvemazana

na Junming Chen

Mutengi: Chen junming

Mukundi weMubairo weSimbi we A' Design Award muChikwata cheJeneretivu

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Nezvekwa Technology Inheritance Chinangwa Chikuru: Chishandiso Chekugadzira Zvivakwa Zvemazana

Rugwaro rweBhuku: Nhaka yeThekinoroji chishandiso che artificial intelligence chinogadzira zvivakwa zvekunze kwedzimba. Chishandiso ichi chinogadzira zvionekwa zvedzimba mumagariro akasiyana-siyana emhando yekuvaka kubva pamavara anonyorwa nemushandisi. Mufananidzo wega wega unogadzirwa mumasekondi mashoma, uye gadziriro inogona kuchinjwa nekugadzirisa rondedzero yemavara. Sisitimu iyi yakavakwa nekuunganidza uye kuisa mazita pamafananidzo ezvivakwa zvinosvika muzviuru, ozoita kugadzirisa modhi yekugadzira mifananidzo yaivepo netsva dhata seti. Chinangwa ndechekubatsira vatangi kusvika padanho repamusoro rehunyanzvi.

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Nezve Mubairo weSimbi we A' Design Award

Mubairo weSimbi we A' Design Award wakahwinwa ne Technology Inheritance Chinangwa Chikuru: Chishandiso Chekugadzira Zvivakwa Zvemazana, rukudzo runokudzwa runopiwa kumadhizaini akanaka anozadzisa zvinodiwa zvehunyanzvi neyeindasitiri zvinotarisirwa kuzvigadzirwa zvakagadzirwa zvakanaka. Vakunda veSimbi vanoratidza unyanzvi hukuru, hunyanzvi hwakakwirira, kunzwisisa kwevakachenjera uye kugona kwekugadzira kwevagadziri vavo. Technology Inheritance Chinangwa Chikuru: Chishandiso Chekugadzira Zvivakwa Zvemazana inotarisirwa kuva chigadzirwa chinokudzwa zvakanyanya, chinoremekedzwa uye chinodiwa, chinoshanda uye chine zvitsva. Dhizaini iyi yakahwina Mubairo weSimbi we A' Design Award inosanganisa maitiro akanakisa eindasitiri uye ine hunhu hwetekinoroji hwakakwana hwakabatana neruzivo nehunyanzvi. Nekushanda kwayo zvakanaka, Technology Inheritance Chinangwa Chikuru: Chishandiso Chekugadzira Zvivakwa Zvemazana inoremekedzwa uye yakagadzirirwa kupa kuvandudzwa kwehupenyu kunobatsira kuita kuti nyika ive nzvimbo iri nani.

Shure kweDhizaini

Bepa Renhau

Zvikwereti, nhengo dzetiimu nezvimwe zvakadzama zvakapihwa nemudhizaina.

Hunhu Hwakasiyana: 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.
Kukura & Kupakiwa: Generating building exteriors using a fine-tuned stable diffusion technique.
Matagi: Artificial intelligence, Human-computer cooperation, Architectural appearance generation, Text generation design, Quick modification, Architectural style control
Tekinoroji Yekugadzira: 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.
Changamire yeDhizaini: 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.
Tsvakurudzo: 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.
Chikurudziro: 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.
Nguva yePurojekiti: The project has already been completed in 2023.
Mafambiro eBasa: 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.