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Generate Images from Lines Gineadóir Dearaidh Intí by Junming Chen

Generate Images from Lines Gineadóir Dearaidh Intí by Junming Chen is a highly esteemed winner of the very prestigious 2023 Duais Iarainn A' Design Award in Dealbhadh Gineadach, Algairimach, Parameatrach agus le Taic AI Competition Category.


IarannGineadach· 2023

Generate Images from Lines Gineadóir Dearaidh Intí

by Junming Chen

Client: Junming Chen

Duais Iarainn A' Design Award Winner in Gineadach Category

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Verified Award Winner

Verify Award Status for #150690

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The Design

About Generate Images from Lines Gineadóir Dearaidh Intí

Gineann Íomhánna ó Línte córas intleachta saorga a chruthaíonn rindreálacha dearaidh intí ó línealacha. Tá an córas bunaithe ar mhúnla idirleata feabhsaithe, oilte ar bhreis agus 20,000 íomhá dearaidh intí a bailíodh agus a nótáladh ag dearthóirí gairmiúla. Cuireann dearthóirí dréacht líne lámhtharraingthe nó digiteach isteach agus roghnaíonn siad stíl mhaisiúcháin, mar shampla nua-aimseartha, Seapánach, Eorpach nó Sínis. Táirgtear rindreáil laistigh de chúpla soicind. Athraítear dearaí trí eagarthóireacht a dhéanamh ar an dréacht líne, agus dá bhrí sin níl gá le múnlú lámhach ná athrindreáil.

The Recognition

About the Duais Iarainn A' Design Award

Tha Generate Images from Lines Gineadóir Dearaidh Intí air Duais Iarainn A' Design Award a bhuannachadh, aithneachadh urramach a bheirear do dhealbhaidhean math a choinnicheas ris na riatanasan proifeiseanta is gnìomhachais a thathar a' sùileachadh bho chruthachaidhean a chaidh an dealbhadh gu math. Tha buannaichean Iarainn a' nochdadh sgil mhòr, speisealachadh àrd, tuigse eòlaiche agus comas cruthachail an luchd-cruthachaidh. Thathar an dùil gum bi Generate Images from Lines Gineadóir Dearaidh Intí na chruthachadh air a bheil mòran meas, ion-mholta agus gràdhach a tha practaigeach agus ùr-ghnàthach. Tha an dealbhadh seo a bhuannaich Duais Iarainn A' Design Award a' cur nan cleachdaidhean as fheàrr sa ghnìomhachas còmhla agus tha feartan teignigeach comasach aige ceangailte ri eòlas-dèanamh agus tàlant. Tha meas air Generate Images from Lines Gineadóir Dearaidh Intí airson a dhùrachd agus chaidh a dhealbhadh gus leasachaidhean càileachd beatha a thoirt seachad a chuidicheas le bhith a' dèanamh an t-saoghail na àite nas fheàrr.

Behind the Design

Press Kit

Credits, team members and technical details provided by the designer.

Unique Properties
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.
Dimensions & Packaging
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.
Tags
Artificial intelligence, Human-machine collaboration, Interior design, Generative design, Efficient design, Rapid modification, Controllable design, Decoration style control
Production Technology
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.
Design Challenge
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.
Research
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.
Inspiration
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.
Project Duration
The project is located in Guangzhou, Guangdong Province, China, and was designed in 2023.
Operation Flow
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.

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