sraeli AI company D-ID, which provided technology for projects like Deep Nostalgia, is launching a new platform where users can upload a single image and text to generate video. With this new site called Creative Reality Studio, the company is targeting sectors like corporate training and education, internal and external communication from companies, product marketing and sales.
The platform is pretty simple to use: Users can upload an image of a presenter or select one from the pre-created presenters to start the video creation process. Paid users can access premium presenters who are more “expressive” as they have better facial expressions and hand movements than the default ones. After that, users can either type the text from a script or simply upload an audio clip of someone’s speech. Users can then select a language (the platform supports 119 languages), voice and styles like cheerful, sad, excited and friendly.
The company’s AI-based algorithms will generate a video based on these parameters. Users can then distribute the video anywhere. The firm claims that the algorithm takes only half of the video duration time to generate a clip, but in our tests, it took a couple of minutes to generate a one-minute video. This could change depending on the type of presenter and language you selected. Read More
Tag Archives: Image Recognition
Midjourney AI Art VS Artist – Testing Ai art to see if it can replicate my artwork
Transframer: Arbitrary Frame Prediction with Generative Models
We present a general-purpose framework for image modelling and vision tasks based on probabilistic frame prediction. Our approach unifies a broad range of tasks, from image segmentation, to novel view synthesis and video interpolation. We pair this framework with an architecture we term Transframer, which uses U-Net and Transformer components to condition on annotated context frames, and outputs sequences of sparse, compressed image features. Transframer is the state-of-the-art on a variety of video generation benchmarks, is competitive with the strongest models on few-shot view synthesis, and can generate coherent 30 second videos from a single image without any explicit geometric information. A single generalist Transframer simultaneously produces promising results on 8 tasks, including semantic segmentation, image classification and optical flow prediction with no task-specific architectural components, demonstrating that multi-task computer vision can be tackled using probabilistic image models. Our approach can in principle be applied to a wide range of applications that require learning the conditional structure of annotated image-formatted data Read More
#big7, #image-recognitionUpcoming AI image generator will run on an RTX 3080
An announcement from Stability.ai comes with some great news for anyone on the AI image generation hype. Stable Diffusion, an image generation software that uses consumer level hardware, will soon be going public. Read More
#image-recognitionYou can (sort of) generate art like Dall-E with TikTok’s latest filter
If
you’re still on the waiting list to try out DALL-E and you just want a quick peek at the kind of technology that powers it, you might want to open up TikTok.
TikTok’s latest filter may have been around for a few days now, but we first noticed its new A.I. text-to-image generator filter on Sunday. It’s called AI Greenscreen, and it lets you generate painterly style images based on words you input. And the images you generate can become the background of your TikTok videos, like a green screen. Read More
Midjourney’s enthralling AI art generator goes live for everyone
The only catch is that you’ll need a Discord account to make your own spectacular art.
One of the more evocative platforms for AI art, Midjourney, has now opened to everyone in beta mode.
This is the second time that the platform has opened to all as a beta. On July 18, the platform opened up for 24 hours. In an email sent out to Midjourney beta testers on Tuesday, however, founder David Holz wrote that the “Midjourney beta is now open to everyone.” Read More
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Commercial image-generating AI raises all sorts of thorny legal issues
This week, OpenAI granted users of its image-generating AI system, DALL-E 2, the right to use their generations for commercial projects, like illustrations for children’s books and art for newsletters. The move makes sense, given OpenAI’s own commercial aims — the policy change coincided with the launch of the company’s paid plans for DALL-E 2. But it raises questions about the legal implications of AI like DALL-E 2, trained on public images around the web, and their potential to infringe on existing copyrights. Read More
Meta’s latest generative AI system creates stunning images from sketches and text
Meta Platforms Inc. today unveiled an advanced “generative artificial intelligence system” that’s designed to help artists better showcase their creativity.
The system, called “Make-A-Scene,” is meant to demonstrate how AI has the potential to empower anyone to bring their imagination to life. The user can simply describe and illustrate their vision through a combination of text descriptions and freeform sketches, and the AI will come up with a stunning representation of it. Read More
DALL-E Mini Is the Internet’s Favorite AI Meme Machine
Hugging Face, a company that hosts open source artificial intelligence projects, saw traffic to an AI image-generation tool called DALL-E Mini skyrocket.
The outwardly simple app, which generates nine images in response to any typed text prompt, was launched nearly a year ago by an independent developer. But after some recent improvements and a few viral tweets, its ability to crudely sketch all manner of surreal, hilarious, and even nightmarish visions suddenly became meme magic. Behold its renditions of “Thanos looking for his mom at Walmart,” “drunk shirtless guys wandering around Mordor,” “CCTV camera footage of Darth Vader breakdancing,” and “a hamster Godzilla in a sombrero attacking Tokyo.” Read More
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Google engineer identifies anonymous faces in WWII photos with AI facial recognition
Walking past the countless photos of Holocaust survivors and victims at Warsaw’s POLIN Museum of the History of Polish Jews in 2016, New York-native Daniel Patt was haunted by the possibility that he was passing the faces of his own relatives without even knowing it.
For Patt, a 40-year-old software engineer now working for Google, that sort of conundrum presented the potential for a creative solution. And so he set to work creating and developing From Numbers to Names (N2N), an artificial intelligence-driven facial recognition platform that can scan through photos from prewar Europe and the Holocaust, linking them to people living today. Read More
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