Generate Images from Lines Ġeneratur tad-Disinn tal-Interjuri minn Junming Chen

Id-disinn Generate Images from Lines Ġeneratur tad-Disinn tal-Interjuri minn Junming Chen huwa rebbieħ stmat ħafna tal-prestiġjuż 2023 Premju A' Design Award tal-Ħadid fil-Kategorija tal-Kompetizzjoni ta' Disinn Ġenerattiv, Algoritmiku, Parametriku u Assistit mill-AI.

ĦadidĠenerattiv· 2023

Generate Images from Lines Ġeneratur tad-Disinn tal-Interjuri

minn Junming Chen

Klijent: Junming Chen

Rebbieħ tal-Premju A' Design Award tal-Ħadid fil-Kategorija ta' Ġenerattiv

48,097

Rebbieħ ta' Premju Ivverifikat

Ivverifika l-Istatus tal-Premju għal #150690

Ara fuq A' Design Award Stqarrija għall-Istampa Badge tal-Premju

Kuluri

Id-Disinn

Dwar Generate Images from Lines Ġeneratur tad-Disinn tal-Interjuri

Iġġenera Immaġnijiet minn Linji hija sistema ta' intelliġenza artifiċjali li toħloq rendering tad-disinn tal-interjuri minn tpinġijiet bil-linji. Is-sistema hija bbażata fuq mudell tad-diffużjoni mtejjeb, imħarreġ fuq aktar minn 20,000 immaġni tad-disinn tal-interjuri miġbura u annotati minn diżinjaturi professjonali. Id-diżinjaturi jdaħħlu abbozz bil-linji miktub bl-idejn jew diġitali u jagħżlu stil dekorattiv, bħal modern, Ġappuniż, Ewropew jew Ċiniż. Rendering jiġi prodott f'ftit sekondi. Id-disinji jinbidlu billi jiġi editjat l-abbozz bil-linji, għalhekk mudellar manwali u rendering mill-ġdid ma jkunux meħtieġa.

Ir-Rikonoxximent

Dwar il-Premju A' Design Award tal-Ħadid

Generate Images from Lines Ġeneratur tad-Disinn tal-Interjuri huwa rebbieħ tal-Premju A' Design Award tal-Ħadid, rikonoxximent prestiġjuż mogħti lil disinji tajbin li jissodisfaw ir-rekwiżiti professjonali u industrijali mistennija minn ħolqien imfassal tajjeb. Ir-rebbieħa tal-Ħadid juru l-ħila kbira, l-ispeċjalizzazzjoni għolja, il-fehim espert u l-kapaċità kreattiva tal-ħallieqa tagħhom. Huwa mistenni li Generate Images from Lines Ġeneratur tad-Disinn tal-Interjuri ikun ħolqien imqabbar ħafna, mammirat u maħbub li huwa prattiku u innovattiv. Dan id-disinn rebbieħ tal-Ħadid jintegra l-aħjar prattiki tal-industrija u għandu karatteristiċi tekniċi kompetenti marbuta mal-għarfien u t-talent. Generate Images from Lines Ġeneratur tad-Disinn tal-Interjuri huwa rispettat għall-eżattezza tiegħu u mfassal biex itejjeb il-kwalità tal-ħajja u jgħin jagħmel id-dinja post aħjar.

Wara d-Disinn

Kit għall-Istampa

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Proprjetajiet Uniċi: 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.
Dimensjonijiet u Ippakkjar: 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.
Tikketti: Artificial intelligence, Human-machine collaboration, Interior design, Generative design, Efficient design, Rapid modification, Controllable design, Decoration style control
Teknoloġija tal-Produzzjoni: 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.
Sfida tad-Disinn: 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.
Riċerka: 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.
Ispirazzjoni: 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.
Tul tal-Proġett: The project is located in Guangzhou, Guangdong Province, China, and was designed in 2023.
Fluss tal-Operazzjoni: 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.