Only Text Kaiwhakaputa Hoahoa Roro Whare Whakaahua nā Zichun Shao

Ko te hoahoa Only Text Kaiwhakaputa Hoahoa Roro Whare Whakaahua nā Zichun Shao he kaitoa whakahirahira o te 2023 A' Design Award Rino i te Wāhanga Whakataetae Hoahoa Hanga, Hātepe, Tawhā me te AI-Āwhina.

RinoHoahoa Hanga· 2023

Only Text Kaiwhakaputa Hoahoa Roro Whare Whakaahua

nā Zichun Shao

Kiritaki: Zichun Shao

Kaitoa o te A' Design Award Rino i te Wāhanga Hoahoa Hanga

44,535

Kaitoa Tohu Manatokohia

Manatokohia te Tūnga Tohu mō #150725

Tirohia i te A' Design Award Pānui Pāpāho Tohu Tohu

Ngā Tae

Te Hoahoa

Mō Only Text Kaiwhakaputa Hoahoa Roro Whare Whakaahua

Ko Only Text he taputapu hoahoa whakaputa e hanga ana i ngā whakaahua hoahoa roro whare mai i ngā whakaahuatanga tuhituhi. Ko te taputapu nei e ahu mai ana i tētahi tauira "diffusion" i whakangungua mō te hoahoa roro whare ngaio. Neke atu i te 20,000 ngā whakaahua roro whare i kohikohia, i tapaina hoki e ngā kaihoahoa hei hanga i te huinga raraunga whakangungu. Ka taea e Only Text te whakaputa i tētahi tirohanga roro whare i roto i ētahi hēkona, me te momo whakapaipai me ngā āhuatanga o te wāhi kua whiriwhiria. Ka whakarerekētia ngā taipitopito mā te whakatika i te kuputuhi, ka whakaputa anō ai. Mā tēnei tikanga e tango ai te hanga tauira ā-ringa me te whakaputa āhua, nā reira ka taea te tohatoha tere i ngā kōwhiringa maha ki ngā kiritaki.

Te Whakamihi

Mō te A' Design Award Rino

Ko Only Text Kaiwhakaputa Hoahoa Roro Whare Whakaahua te toa o te A' Design Award Rino, he whakaaetanga whai mana e hoatu ana ki ngā hoahoa pai e whakatutuki ana i ngā hiahia ngaio me te ahumahi e tūmanakohia ana mai i ngā mahi kua hoahoatia pai. Ko ngā toa Rino e whakaatu ana i te pukenga nui, te tohungatanga teitei, te māramatanga mātanga me te kaha auaha o ō rātou kaihanga. E tūmanakohia ana ko Only Text Kaiwhakaputa Hoahoa Roro Whare Whakaahua he mahi whakanuia, whakamīharotia, aroha nui, he whaihua, he auaha hoki. Ko tēnei hoahoa i toa i te Rino e whakakotahi ana i ngā tikanga pai rawa o te ahumahi, ā, he āhuatanga hangarau pūkenga tōna e hono ana ki te mōhio me te pūmanawa. E whakahonoretia ana a Only Text Kaiwhakaputa Hoahoa Roro Whare Whakaahua mō tōna tōtika, ā, i hoahoatia hei whakapai ake i te kounga o te oranga me te āwhina i te ao kia pai ake.

I Muri i te Hoahoa

Kete Pāpāho

Ngā whakamihi, ngā mema o te rōpū me ngā taipitopito hangarau i whakaratohia e te kaihoahoa.

Āhuatanga Motuhake: The design was done by artificial intelligence (AI) in collaboration with designers. This project has trained an AI for professional interior design generation, which can generate interior designs with different decoration styles according to the input text. It only takes a few seconds for AI to generate a new interior design, and it can quickly generate a large number of designs for communication with users, thereby improving design efficiency.
Inenga & Pēketanga: The project uses diffusion model technology, using artificial intelligence to cooperate with designers to generate designs of different decorative styles. We retrained a professional interior design AI to quickly create designs with varying decoration styles.
Tūtohu: Artificial intelligence, Human-computer collaboration, Interior design, Generative design, Text generative design, Efficient design, Rapid modification, Controllable design, Decoration style control
Hangarau Whakanao: Ordinary AI cannot generate interior design according to specific "decoration style" and "space attributes," which is a fatal flaw for interior design. To this end, this project collected more than 20,000 interior design renderings, labeled them to make a data set and gave the data set to AI for learning, thus creating an AI suitable for interior design. The AI can generate interior renderings specifying "decorative style" and "space attributes" by inputting text.
Wero Hoahoa: 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, this project 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.
Rangahau: Research Background: Interior design communication is complex, and obtaining designs and communicating with customers quickly is necessary.
Methods: This project trained an AI to generate interior designs professionally and used the AI to collaborate with humans to create interior designs in various decorative styles from the text.
Results: Using the AI trained in this project, designers can generate an interior design rendering in just a few seconds.
Insights: This project approach rapidly generates large batches of interior designs for specified decor styles and spatial properties and allows new designs to be generated by modifying text. This method eliminates the need for manual modeling and rendering, which improves design efficiency.
Whakaaweawe: It is difficult for users to imagine the scheme described by the designer in words. Designers need to turn thinking into design quickly. With the development of artificial intelligence (AI), designers can generate designs directly from text. Specifically, this project trained an AI to create interior design, which can generate interior design only by inputting text, improving communication efficiency between designers and users.
Roanga o te Kaupapa: The project is located in Guangzhou, Guangdong Province, China, and was designed in 2023.
Rerenga Mahi: 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 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.