AI for Learning Photorealistic 3D Digital Humans from In-the-Wild Data - Livestream

Traditionally, creating 3D digital humans requires lengthy efforts by digital artists, and often costly 3D scanning by special multi-view scanners. Learn how recent generative AI technologies allow the learning of photorealistic 3D representations from a collection of in-the-wild 2D images, such as internet photos. We'll dive deep into our recent work called “EG3D” and “WYSIWYG”, which can synthesize wide varieties of photorealistic 3D humans in real time. We'll also show how 3D synthetic data from a pre-trained 3D generative model can be used to train another AI model for challenging image synthesis tasks. To this end, we present our recent work called “LP3D,” which can synthesize photorealistic neural radiance field (NeRF) models from a single RGB image in real time. We'll demonstrate how these AI-driven human synthesis methods can make the advanced capabilities, such as 3D video conferencing, accessible to anyone and enable new applications in the future.

Speaker: Matthew Chan, NIVIDIA

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