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Transform Your Images into Dynamic Videos with Google's VLOGGER AI

With Artificial Intelligence (AI) being the hottest buzzword in technology, researchers at search engine giant Google have been busy, revealing a series of new images and concepts in their latest creation by turning static images into mutable avatars, a new version of their game -creating AI -Tracks progress.

Even if Google VLOGGER can’t continue testing, as per multiple reports, it can allow users to create and control avatars via voice commands.

However, user X named Madni Aghadi (@hey_madni), first posted on Twitter:

"Google just dropped VLOGGER, and it's crazy. It will change the future of VIDEO forever. Here's everything you need to stay ahead of the curve: and it does.”

It should be noted that the picture posted by Aghadi is fake and not real. VLOGGER is the tech giant's research project that may be able to "create images" using AI in the future. While existing tools like Pika Lab's “Lip Sync”, Hey Gen Video Translation Services, and Synthesia offer similar functionality to some extent, Google VLOGGER seems to offer a more straightforward, bandwidth-friendly alternative.

What is a VLOGGER

Currently, VLOGGER is an exploratory effort along with a few interesting demo videos. But if it takes shape, platforms like Teams or Slack have the potential to revolutionize communication.

This AI model can create a dynamic avatar from a static image, and the photorealistic look of the person is preserved in every frame of the resulting video.

Additionally, the model integrates an audio file of the person speaking, organizing body and lip movements to show natural gestures and facial expressions as if speaking in real life. This also includes moving the head, facial expressions, eye movements, blinking, hand gestures, and upper body movements, all this without relying on any other contextual information beyond images and audio it has been given to him.

A Github post further explains VLOGGER (basically): "We propose VLOGGER, a platform for creating human videos of stories and conversations using audio from a single human image input, built on success" on the recent reproductive expansion model.

Our approach includes 1) a stochastic human-to-3d motion diffusion model, and 2) a new diffusion-based architecture that enhances the text-to-model with temporal and spatial control. This approach enables high-quality videos a variable lengths, which are easily controllable through the high-level rendering of the human face and body.

Unlike the previous work, our method does not need to train each person, but it relies on face recognition and cropping along with providing a complete image.

Conclusion: As the digital landscape continues to evolve, VLOGGER emerges as a game-changer, democratizing video production and redefining the boundaries of visual storytelling. Thanks to Google’s commitment to innovation and possibility, VLOGGER sets a new standard for AI-enabled production tools, empowering creators of all backgrounds to bring their ideas to life in ways never before imagined.