22 citations · 33 across the 2 of their papers we have counts for
7 papers
Mixture of Volumetric Primitives for Efficient Neural Rendering
Stephen Lombardi, Tomas Simon, Gabriel Schwartz +3
Real-time rendering and animation of humans is a core function in games, movies, and telepresence applications. Existing methods have a number of drawbacks we aim to address with o…
PVA: Pixel-aligned Volumetric Avatars
Amit Raj, Michael Zollhoefer, Tomas Simon +4
Acquisition and rendering of photo-realistic human heads is a highly challenging research problem of particular importance for virtual telepresence. Currently, the highest quality…
Learning Compositional Radiance Fields of Dynamic Human Heads
Ziyan Wang, Timur Bagautdinov, Stephen Lombardi +4
Photorealistic rendering of dynamic humans is an important ability for telepresence systems, virtual shopping, synthetic data generation, and more. Recently, neural rendering metho…
State of the Art on Neural Rendering
Ayush Tewari, Ohad Fried, Justus Thies +16
Efficient rendering of photo-realistic virtual worlds is a long standing effort of computer graphics. Modern graphics techniques have succeeded in synthesizing photo-realistic imag…
Neural Volumes: Learning Dynamic Renderable Volumes from Images
Stephen Lombardi, Tomas Simon, Jason Saragih +3
Modeling and rendering of dynamic scenes is challenging, as natural scenes often contain complex phenomena such as thin structures, evolving topology, translucency, scattering, occ…
Deep Appearance Models for Face Rendering
Stephen Lombardi, Jason Saragih, Tomas Simon +1
We introduce a deep appearance model for rendering the human face. Inspired by Active Appearance Models, we develop a data-driven rendering pipeline that learns a joint representat…