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Drupal\cryptocompare\TwigExtension\RemoveSpace::getcard(' 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>. <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. HOT Stories <a rel="nofollow" target="_blank" class="btn btn--light hot__btn" href="/hot-stories" title="Go to Hot stories"> </a> <a href="https://u.today/cardano-founder-says-iogs-ada-is-not-peoples-money" class="hot__col"> Cardano Founder Says IOG's ADA Is Not People's Money </a> <a href="https://u.today/shib-burns-jump-300-but-shib-army-demands-much-bigger-burns" class="hot__col"> SHIB Burns Jump 300% but SHIB Army Demands Much Bigger Burns </a> <a href="https://u.today/bitcoins-1st-tweet-at-0-marks-16-years-details" class="hot__col"> Bitcoin's 1st Tweet at $0 Marks 16 Years: Details </a> <a href="https://u.today/xrp-chart-pattern-warns-of-incoming-xrp-price-swings" class="hot__col"> XRP Chart Pattern Warns of Incoming XRP Price Swings </a> Advertisement <a href="https://u.today/events/convergence-blockchain-artificial-intelligence">card</a> 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 <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. <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. On top of that, the researches also failed to include certain ethnicities in the study to make the technique more universal. ') (Line: 1226) Drupal\cryptocompare\TwigExtension\RemoveSpace->formatbody(Array) (Line: 54) __TwigTemplate_75845256f703f5319a38e035b4af7dd9->doDisplay(Array, Array) (Line: 394) Twig\Template->displayWithErrorHandling(Array, Array) (Line: 367) Twig\Template->display(Array) (Line: 379) Twig\Template->render(Array, Array) (Line: 40) Twig\TemplateWrapper->render(Array) (Line: 53) 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: 1250) __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) Twig\Template->displayWithErrorHandling(Array, Array) (Line: 367) Twig\Template->display(Array) (Line: 379) Twig\Template->render(Array, Array) (Line: 40) Twig\TemplateWrapper->render(Array) (Line: 53) twig_render_template('themes/cryptod/templates/node.html.twig', Array) (Line: 372) 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) Drupal\Core\Render\MainContent\HtmlRenderer->Drupal\Core\Render\MainContent\{closure}() (Line: 583) 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) Drupal\Component\EventDispatcher\ContainerAwareEventDispatcher->dispatch(Object, 'kernel.view') (Line: 187) Symfony\Component\HttpKernel\HttpKernel->handleRaw(Object, 1) (Line: 76) Symfony\Component\HttpKernel\HttpKernel->handle(Object, 1, 1) (Line: 58) Drupal\Core\StackMiddleware\Session->handle(Object, 1, 1) (Line: 48) Drupal\Core\StackMiddleware\KernelPreHandle->handle(Object, 1, 1) (Line: 191) Drupal\page_cache\StackMiddleware\PageCache->fetch(Object, 1, 1) (Line: 128) 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) - Warning: Undefined variable $authorImageUrl in Drupal\cryptocompare\TwigExtension\RemoveSpace::getcard() (line 3496 of modules/custom/cryptocompare/src/TwigExtension/RemoveSpace.php).
Drupal\cryptocompare\TwigExtension\RemoveSpace::getcard(' 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>. <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. HOT Stories <a rel="nofollow" target="_blank" class="btn btn--light hot__btn" href="/hot-stories" title="Go to Hot stories"> </a> <a href="https://u.today/cardano-founder-says-iogs-ada-is-not-peoples-money" class="hot__col"> Cardano Founder Says IOG's ADA Is Not People's Money </a> <a href="https://u.today/shib-burns-jump-300-but-shib-army-demands-much-bigger-burns" class="hot__col"> SHIB Burns Jump 300% but SHIB Army Demands Much Bigger Burns </a> <a href="https://u.today/bitcoins-1st-tweet-at-0-marks-16-years-details" class="hot__col"> Bitcoin's 1st Tweet at $0 Marks 16 Years: Details </a> <a href="https://u.today/xrp-chart-pattern-warns-of-incoming-xrp-price-swings" class="hot__col"> XRP Chart Pattern Warns of Incoming XRP Price Swings </a> Advertisement <a href="https://u.today/events/convergence-blockchain-artificial-intelligence">card</a> 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 <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. <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. On top of that, the researches also failed to include certain ethnicities in the study to make the technique more universal. ') (Line: 1226) Drupal\cryptocompare\TwigExtension\RemoveSpace->formatbody(Array) (Line: 54) __TwigTemplate_75845256f703f5319a38e035b4af7dd9->doDisplay(Array, Array) (Line: 394) Twig\Template->displayWithErrorHandling(Array, Array) (Line: 367) Twig\Template->display(Array) (Line: 379) Twig\Template->render(Array, Array) (Line: 40) Twig\TemplateWrapper->render(Array) (Line: 53) 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: 1250) __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) Twig\Template->displayWithErrorHandling(Array, Array) (Line: 367) Twig\Template->display(Array) (Line: 379) Twig\Template->render(Array, Array) (Line: 40) Twig\TemplateWrapper->render(Array) (Line: 53) twig_render_template('themes/cryptod/templates/node.html.twig', Array) (Line: 372) 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) Drupal\Core\Render\MainContent\HtmlRenderer->Drupal\Core\Render\MainContent\{closure}() (Line: 583) 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) Drupal\Component\EventDispatcher\ContainerAwareEventDispatcher->dispatch(Object, 'kernel.view') (Line: 187) Symfony\Component\HttpKernel\HttpKernel->handleRaw(Object, 1) (Line: 76) Symfony\Component\HttpKernel\HttpKernel->handle(Object, 1, 1) (Line: 58) Drupal\Core\StackMiddleware\Session->handle(Object, 1, 1) (Line: 48) Drupal\Core\StackMiddleware\KernelPreHandle->handle(Object, 1, 1) (Line: 191) Drupal\page_cache\StackMiddleware\PageCache->fetch(Object, 1, 1) (Line: 128) 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
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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.
Advertisement
Related
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.
Related
Sun, 11/11/2018 - 09:14
Artificial Intelligence: Usurped and Trapped, But Not For Much Longer
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.
Disclaimer: The opinions expressed by our writers are their own and do not represent the views of U.Today. The financial and market information provided on U.Today is intended for informational purposes only. U.Today is not liable for any financial losses incurred while trading cryptocurrencies. Conduct your own research by contacting financial experts before making any investment decisions. We believe that all content is accurate as of the date of publication, but certain offers mentioned may no longer be available.
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