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                    <ul class="article__contents-list"><li class="article__contents-item"><a class="article__contents-link link-pseudo" href="#h220582">200 pictures for training an AI system  </a></li><li class="article__contents-item"><a class="article__contents-link link-pseudo" href="#h320582">AvatarMe is not without flaws</a></li></ul>
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A group of researchers from Imperial College London has come up with a way to render 3D faces from a single picture with the help of artificial intelligence, <a rel="nofollow" target="_blank" href="https://venturebeat.com/2020/06/16/ai-model-creates-3d-avatars-from-a-persons-picture/">VentureBeat reports</a>.&nbsp;&nbsp;



<a rel="nofollow" target="_blank" href="https://arxiv.org/pdf/2003.13845.pdf">Their paper</a> made its way to the ongoing CVPR conference, which is being held in a virtual format from June 14 to June 19.&nbsp;&nbsp;
    
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&nbsp;

<a href="https://u.today/events/convergence-blockchain-artificial-intelligence">card</a>

200 pictures for training an AI system&nbsp;&nbsp;

The described technique, called AvatarMe, represents the very first methodology that allows creating high-quality render-ready 3D busts from nothing but arbitrary images.

The researches deployed a training dataset that consists of 200 pictures of people’s faces that were acquired with the help of ‘state-of-the-art’ facial capture methods.

Those individuals whose photos were used in the experiment belong to different age groups and have different characteristics.&nbsp;&nbsp;

This data collection was necessary for training GANFIT, an <a href="https://u.today/meet-velas-when-artificial-intuition-boosts-blockchain-capabilities">AI model</a> at the core of the experiment that is used for inferring information about texture and shape from a single image.&nbsp;

<a href="https://u.today/artificial-intelligence-usurped-and-trapped-but-not-for-much-longer">card</a>

AvatarMe is not without flaws

AvatarMe was able to avoid artifacts even when trying different poses and occlusions. It was possible to realistically reconstruct portraits and black-and-white photographs.

However, it is worth noting that AvatarMe still shows poorer results with input phonographs of lower quality.&nbsp;

On top of that, the researches also failed to include certain ethnicities in the study to make the technique more universal.&nbsp;&nbsp;&nbsp;
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Drupal\Core\Template\TwigExtension->escapeFilter(Object, Array, 'html', NULL, 1) (Line: 866)
__TwigTemplate_625426e732c5f7a66fde6d628d98a6b2->doDisplay(Array, Array) (Line: 394)
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Drupal\Core\Render\Renderer->doRender(Array, ) (Line: 204)
Drupal\Core\Render\Renderer->render(Array, ) (Line: 238)
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Drupal\Core\DrupalKernel->handle(Object) (Line: 18)
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                    <ul class="article__contents-list"><li class="article__contents-item"><a class="article__contents-link link-pseudo" href="#h220582">200 pictures for training an AI system  </a></li><li class="article__contents-item"><a class="article__contents-link link-pseudo" href="#h320582">AvatarMe is not without flaws</a></li></ul>
    Advertisement
    
        
    
   
        
                
            
                                                

                                    
    

        
        
                
            
                                                

                                    
    

        
    
A group of researchers from Imperial College London has come up with a way to render 3D faces from a single picture with the help of artificial intelligence, <a rel="nofollow" target="_blank" href="https://venturebeat.com/2020/06/16/ai-model-creates-3d-avatars-from-a-persons-picture/">VentureBeat reports</a>.&nbsp;&nbsp;



<a rel="nofollow" target="_blank" href="https://arxiv.org/pdf/2003.13845.pdf">Their paper</a> made its way to the ongoing CVPR conference, which is being held in a virtual format from June 14 to June 19.&nbsp;&nbsp;
    
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    Ripple CTO Shares Hilarious Email from Jed McCaleb Impersonator 
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</a>


    





    Advertisement
    
        
    
    
        
                
            
                                                

                                    
    

        
        
                
            
                                                

                                    
    

        
    


&nbsp;

<a href="https://u.today/events/convergence-blockchain-artificial-intelligence">card</a>

200 pictures for training an AI system&nbsp;&nbsp;

The described technique, called AvatarMe, represents the very first methodology that allows creating high-quality render-ready 3D busts from nothing but arbitrary images.

The researches deployed a training dataset that consists of 200 pictures of people’s faces that were acquired with the help of ‘state-of-the-art’ facial capture methods.

Those individuals whose photos were used in the experiment belong to different age groups and have different characteristics.&nbsp;&nbsp;

This data collection was necessary for training GANFIT, an <a href="https://u.today/meet-velas-when-artificial-intuition-boosts-blockchain-capabilities">AI model</a> at the core of the experiment that is used for inferring information about texture and shape from a single image.&nbsp;

<a href="https://u.today/artificial-intelligence-usurped-and-trapped-but-not-for-much-longer">card</a>

AvatarMe is not without flaws

AvatarMe was able to avoid artifacts even when trying different poses and occlusions. It was possible to realistically reconstruct portraits and black-and-white photographs.

However, it is worth noting that AvatarMe still shows poorer results with input phonographs of lower quality.&nbsp;

On top of that, the researches also failed to include certain ethnicities in the study to make the technique more universal.&nbsp;&nbsp;&nbsp;
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Drupal\cryptocompare\TwigExtension\RemoveSpace->formatbody(Array) (Line: 54)
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Twig\Template->displayWithErrorHandling(Array, Array) (Line: 367)
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Drupal\Core\Theme\ThemeManager->render('field', Array) (Line: 436)
Drupal\Core\Render\Renderer->doRender(Array, ) (Line: 204)
Drupal\Core\Render\Renderer->render(Array) (Line: 474)
Drupal\Core\Template\TwigExtension->escapeFilter(Object, Array, 'html', NULL, 1) (Line: 866)
__TwigTemplate_625426e732c5f7a66fde6d628d98a6b2->doDisplay(Array, Array) (Line: 394)
Twig\Template->displayWithErrorHandling(Array, Array) (Line: 367)
Twig\Template->display(Array) (Line: 62)
__TwigTemplate_e934e56c1e459c359b150360c7169113->doDisplay(Array, Array) (Line: 394)
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Twig\Template->render(Array, Array) (Line: 40)
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Drupal\Core\Theme\ThemeManager->render('node', Array) (Line: 436)
Drupal\Core\Render\Renderer->doRender(Array, ) (Line: 204)
Drupal\Core\Render\Renderer->render(Array, ) (Line: 238)
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Drupal\Core\Render\Renderer->executeInRenderContext(Object, Object) (Line: 239)
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call_user_func(Array, Object, 'kernel.view', Object) (Line: 111)
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Drupal\Core\DrupalKernel->handle(Object) (Line: 18)
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                    <ul class="article__contents-list"><li class="article__contents-item"><a class="article__contents-link link-pseudo" href="#h220582">200 pictures for training an AI system  </a></li><li class="article__contents-item"><a class="article__contents-link link-pseudo" href="#h320582">AvatarMe is not without flaws</a></li></ul>
    Advertisement
    
        
    
   
        
                
            
                                                

                                    
    

        
        
                
            
                                                

                                    
    

        
    
A group of researchers from Imperial College London has come up with a way to render 3D faces from a single picture with the help of artificial intelligence, <a rel="nofollow" target="_blank" href="https://venturebeat.com/2020/06/16/ai-model-creates-3d-avatars-from-a-persons-picture/">VentureBeat reports</a>.&nbsp;&nbsp;



<a rel="nofollow" target="_blank" href="https://arxiv.org/pdf/2003.13845.pdf">Their paper</a> made its way to the ongoing CVPR conference, which is being held in a virtual format from June 14 to June 19.&nbsp;&nbsp;
    
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    Ripple CTO Shares Hilarious Email from Jed McCaleb Impersonator 
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</a>

<a href="https://u.today/morning-crypto-report-xrp-to-break-first-etf-1-billion-this-week-shiba-inu-shib-teases-29-price" class="hot__col">
    Morning Crypto Report: XRP to Break First ETF $1 Billion This Week, Shiba Inu (SHIB) Teases 29% Price Upside, Bitcoin to $125,000 Is Main Scenario Now: Bollinger Bands
</a>


    





    Advertisement
    
        
    
    
        
                
            
                                                

                                    
    

        
        
                
            
                                                

                                    
    

        
    


&nbsp;

<a href="https://u.today/events/convergence-blockchain-artificial-intelligence">card</a>

200 pictures for training an AI system&nbsp;&nbsp;

The described technique, called AvatarMe, represents the very first methodology that allows creating high-quality render-ready 3D busts from nothing but arbitrary images.

The researches deployed a training dataset that consists of 200 pictures of people’s faces that were acquired with the help of ‘state-of-the-art’ facial capture methods.

Those individuals whose photos were used in the experiment belong to different age groups and have different characteristics.&nbsp;&nbsp;

This data collection was necessary for training GANFIT, an <a href="https://u.today/meet-velas-when-artificial-intuition-boosts-blockchain-capabilities">AI model</a> at the core of the experiment that is used for inferring information about texture and shape from a single image.&nbsp;

<a href="https://u.today/artificial-intelligence-usurped-and-trapped-but-not-for-much-longer">card</a>

AvatarMe is not without flaws

AvatarMe was able to avoid artifacts even when trying different poses and occlusions. It was possible to realistically reconstruct portraits and black-and-white photographs.

However, it is worth noting that AvatarMe still shows poorer results with input phonographs of lower quality.&nbsp;

On top of that, the researches also failed to include certain ethnicities in the study to make the technique more universal.&nbsp;&nbsp;&nbsp;
') (Line: 1244)
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Twig\Template->render(Array, Array) (Line: 40)
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twig_render_template('themes/cryptod/templates/field--body.html.twig', Array) (Line: 372)
Drupal\Core\Theme\ThemeManager->render('field', Array) (Line: 436)
Drupal\Core\Render\Renderer->doRender(Array, ) (Line: 204)
Drupal\Core\Render\Renderer->render(Array) (Line: 474)
Drupal\Core\Template\TwigExtension->escapeFilter(Object, Array, 'html', NULL, 1) (Line: 866)
__TwigTemplate_625426e732c5f7a66fde6d628d98a6b2->doDisplay(Array, Array) (Line: 394)
Twig\Template->displayWithErrorHandling(Array, Array) (Line: 367)
Twig\Template->display(Array) (Line: 62)
__TwigTemplate_e934e56c1e459c359b150360c7169113->doDisplay(Array, Array) (Line: 394)
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Twig\Template->display(Array) (Line: 379)
Twig\Template->render(Array, Array) (Line: 40)
Twig\TemplateWrapper->render(Array) (Line: 53)
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Drupal\Core\Render\Renderer->doRender(Array, ) (Line: 204)
Drupal\Core\Render\Renderer->render(Array, ) (Line: 238)
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Drupal\Core\Render\Renderer->executeInRenderContext(Object, Object) (Line: 239)
Drupal\Core\Render\MainContent\HtmlRenderer->prepare(Array, Object, Object) (Line: 128)
Drupal\Core\Render\MainContent\HtmlRenderer->renderResponse(Array, Object, Object) (Line: 90)
Drupal\Core\EventSubscriber\MainContentViewSubscriber->onViewRenderArray(Object, 'kernel.view', Object)
call_user_func(Array, Object, 'kernel.view', Object) (Line: 111)
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Symfony\Component\HttpKernel\HttpKernel->handleRaw(Object, 1) (Line: 76)
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Drupal\Core\StackMiddleware\Session->handle(Object, 1, 1) (Line: 48)
Drupal\Core\StackMiddleware\KernelPreHandle->handle(Object, 1, 1) (Line: 191)
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Drupal\page_cache\StackMiddleware\PageCache->lookup(Object, 1, 1) (Line: 82)
Drupal\page_cache\StackMiddleware\PageCache->handle(Object, 1, 1) (Line: 48)
Drupal\Core\StackMiddleware\ReverseProxyMiddleware->handle(Object, 1, 1) (Line: 51)
Drupal\Core\StackMiddleware\NegotiationMiddleware->handle(Object, 1, 1) (Line: 51)
Drupal\Core\StackMiddleware\StackedHttpKernel->handle(Object, 1, 1) (Line: 704)
Drupal\Core\DrupalKernel->handle(Object) (Line: 18)

    Artificial Intelligence Makes It Possible to Create 3D Avatars from One Photo

    By Alex Dovbnya
    Tue, 16/06/2020 - 17:28
    Researches create photorealistic 3D busts from a single image by using artificial intelligence
    Advertisement
    Artificial Intelligence Makes It Possible to Create 3D Avatars from One Photo
    Cover image via stock.adobe.com
    Read U.TODAY on
    Google News
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    A group of researchers from Imperial College London has come up with a way to render 3D faces from a single picture with the help of artificial intelligence, VentureBeat reports.  

    Their paper made its way to the ongoing CVPR conference, which is being held in a virtual format from June 14 to June 19.  

    HOT Stories
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    Ripple CTO Shares Hilarious Email from Jed McCaleb Impersonator
    XRP Now Offered by Vanguard, Bitcoin Price on the Verge of 40% Crash, Dogecoin Prints 528,408% Liquidation Imbalance – Crypto News Digest
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    Advertisement

     

    You Might Also Like
    Title news
    Tue, 06/12/2018 - 13:16
    Convergence: Blockchain + Artificial Intelligence
    By

    200 pictures for training an AI system  

    The described technique, called AvatarMe, represents the very first methodology that allows creating high-quality render-ready 3D busts from nothing but arbitrary images.

    The researches deployed a training dataset that consists of 200 pictures of people’s faces that were acquired with the help of ‘state-of-the-art’ facial capture methods.

    Those individuals whose photos were used in the experiment belong to different age groups and have different characteristics.  

    This data collection was necessary for training GANFIT, an AI model at the core of the experiment that is used for inferring information about texture and shape from a single image. 

    You Might Also Like
    Title news
    Sun, 11/11/2018 - 09:14
    Artificial Intelligence: Usurped and Trapped, But Not For Much Longer
    ByDarryn Pollock

    AvatarMe is not without flaws

    AvatarMe was able to avoid artifacts even when trying different poses and occlusions. It was possible to realistically reconstruct portraits and black-and-white photographs.

    However, it is worth noting that AvatarMe still shows poorer results with input phonographs of lower quality. 

    On top of that, the researches also failed to include certain ethnicities in the study to make the technique more universal.   

    Advertisement

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