A new Artificial Intelligence (AI) algorithm can now generate high-resolution, photorealistic images of people from scratch which do not exist.
Called as Generative Adversarial Network (GAN), this new class of machine learning systems can generate photographs that look at least superficially authentic to human observers having many realistic characteristics -- faces, hair, outfits, and all. The only thing that these AI-generated people "Do Not Exist" in reality and fashion brands or advertising agencies can use these photogenic AI generated models without paying for lights or a catering budget, which means ditching the fashion models that are actual humans.
[video width="3072" height="1024" mp4="https://www.indianweb2.com/wp-content/uploads/2019/05/full-body-model.mp4"][/video]
Datagrid, a tech company housed on the campus of Japan’s Kyoto University, has developed an AI called "automatic whole-body model generation AI" by applying the GAN based deep learning which learn a large number of whole body model images to generate non-existent whole body model images with high resolution (1024 x 1024) and high quality, which had previously been difficult.
The new kind of AI algorithm typically used to churn out new imitations of something that exists in the real world, whether they be video game levels or images that look like hand-drawn caricatures.
[tnm_video layout="mnmd-post-media-wide"]https://www.youtube.com/watch?v=8siezzLXbNo[/tnm_video]
The Japan-based tech firm had earlier developed idle automatic generation AI in June 2018. However, idle auto generation AI generates an image only for the face area, so it did not have enough expressive power. Therefore, in order to enhance the expressive power of the generated person, Datagrid has been working on two research and development of "whole body generation" and "motion generation". The high-precision whole-body generation model has no precedent, and was a challenging research and development. The company however has now succeeded in stably generating high-resolution (1024 × 1024) whole-body model images.
In its Future Prospects, the company said in a press release that it will further improve the accuracy of the whole-body model automatic generation AI and research and develop the motion generation AI. Additionally, Datagrid will conduct demonstration experiments with advertising and apparel companies to develop functions required for actual operation.
According to critics, GANs potential in human image synthesis can be used for sinister purposes such as to produce fake and/or incriminating photographs and videos and similar algorithms could be misused to undermine public trust in digital media.
A similar AI technology called "Deepfakes", which can doctored images and videos that can be used to generate propaganda and deceptive media like fictionalized political speeches or pornography, is difficult to counter so much so that Canadian Broadcasting Corporation has called it as a matter of national security.
Called as Generative Adversarial Network (GAN), this new class of machine learning systems can generate photographs that look at least superficially authentic to human observers having many realistic characteristics -- faces, hair, outfits, and all. The only thing that these AI-generated people "Do Not Exist" in reality and fashion brands or advertising agencies can use these photogenic AI generated models without paying for lights or a catering budget, which means ditching the fashion models that are actual humans.
[video width="3072" height="1024" mp4="https://www.indianweb2.com/wp-content/uploads/2019/05/full-body-model.mp4"][/video]
Datagrid, a tech company housed on the campus of Japan’s Kyoto University, has developed an AI called "automatic whole-body model generation AI" by applying the GAN based deep learning which learn a large number of whole body model images to generate non-existent whole body model images with high resolution (1024 x 1024) and high quality, which had previously been difficult.
The new kind of AI algorithm typically used to churn out new imitations of something that exists in the real world, whether they be video game levels or images that look like hand-drawn caricatures.
[tnm_video layout="mnmd-post-media-wide"]https://www.youtube.com/watch?v=8siezzLXbNo[/tnm_video]
The Japan-based tech firm had earlier developed idle automatic generation AI in June 2018. However, idle auto generation AI generates an image only for the face area, so it did not have enough expressive power. Therefore, in order to enhance the expressive power of the generated person, Datagrid has been working on two research and development of "whole body generation" and "motion generation". The high-precision whole-body generation model has no precedent, and was a challenging research and development. The company however has now succeeded in stably generating high-resolution (1024 × 1024) whole-body model images.
In its Future Prospects, the company said in a press release that it will further improve the accuracy of the whole-body model automatic generation AI and research and develop the motion generation AI. Additionally, Datagrid will conduct demonstration experiments with advertising and apparel companies to develop functions required for actual operation.
Ethical Disadvantages
According to critics, GANs potential in human image synthesis can be used for sinister purposes such as to produce fake and/or incriminating photographs and videos and similar algorithms could be misused to undermine public trust in digital media.
A similar AI technology called "Deepfakes", which can doctored images and videos that can be used to generate propaganda and deceptive media like fictionalized political speeches or pornography, is difficult to counter so much so that Canadian Broadcasting Corporation has called it as a matter of national security.
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