Meet VLOGGER, a new framework designed by Google Research to synthesize human avatars from audio inputs. Imagine being able to generate photorealistic and temporally coherent videos of a person talking, complete with head motion, gaze, blinking, and even upper-body and hand gestures—all from a single input image and a sample audio.
The Leap Beyond Current Technologies
Unlike previous methods, VLOGGER does not require individual training for each person, nor does it depend on face detection and cropping. It generates the complete image, not just the face or lips, and caters to a broad spectrum of scenarios that are critical for accurately synthesizing humans who communicate.
MENTOR: The Dataset Powering VLOGGER
To achieve this feat, VLOGGER is trained on MENTOR, a new and diverse dataset with 3D pose and expression annotations. This dataset is one order of magnitude larger than previous ones, boasting 800,000 identities and dynamic gestures, which plays a pivotal role in training a fair and unbiased model at scale.
Applications and Future Possibilities
VLOGGER’s potential applications are vast, ranging from video editing and personalization to enhanced online communication, education, and even virtual assistants. Its ability to support natural conversations with a human user positions it as a stand-alone solution for various industries, including content creation, entertainment, and gaming.
As we stand on the brink of a new era in human-computer interaction, one can’t help but wonder:
Do you think VLOGGER and Avatares in general will transform the future of online communication?
In what ways could industries leverage this technology to create more engaging and personalized content?