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Ziva Real-Time’s face trainer is finally blurring the line between reality and CGI

It is not new that it is possible to create hyperrealistic faces or even complete sequences of images with a computer. But CGI technology wasn’t perfect, and even in high-budget movies, it was possible to recognize when digital manipulation started. It’s slowly coming to an end. The line between reality and computer graphics is blurred.

Unreal Engine is best known as the game engine developed by Epic Games and is used in many genres, including first-person shooter (FPS) games, platformers, combat games, MMORPGs and other role-playing games. As early as 2019, the Unreal Engine user group SIGGRAPH showed what it can do in real time by turning LED walls into a lifelike desert to shoot a commercial.

Simply put, this new technology uses real-time camera tracking for seamless blending of actors and scenery using LED walls. Therefore, it appears as if the colors on the projected screen are perfectly reflected in realistic lighting conditions. There is no need to deal with post-production, as everything happens in real time and on camera

But you can go on from here. Ziva Dynamics has officially released the beta version of Real-Time (RT) Face Trainer, a completely amazing, machine-learning, cloud-based face building service for games and real-time work. This Unreal Engine-based tool converts any archiver into a powerful real-time puppet in essentially an hour. It is based on a library of more than 15 TB of 4D scan data, while the generated face puppets can express more than 72,000 practice shapes as well as novel facial poses.

Ziva RT facials are only 30 MB in runtime and run at real-time frame rates (3 ms / frame on a single CPU thread). As for the technical side of things, the mesh has to be manually cleaned and re-topologized to conform to a standard point system before it can be processed and then split to create convincing deformations. ZRT Face Trainer is currently by invitation only. It’s a good luck to think about what you can do with it in the deep fake genre.

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