71 citations · 108 across the 7 of their papers we have counts for
15 papers
LiP-Flow: Learning Inference-time Priors for Codec Avatars via Normalizing Flows in Latent Space
Emre Aksan, Shugao Ma, Akin Caliskan +5
Neural face avatars that are trained from multi-view data captured in camera domes can produce photo-realistic 3D reconstructions. However, at inference time, they must be driven b…
Driving-Signal Aware Full-Body Avatars
Timur Bagautdinov, Chenglei Wu, Tomas Simon +6
We present a learning-based method for building driving-signal aware full-body avatars. Our model is a conditional variational autoencoder that can be animated with incomplete driv…
Pixel Codec Avatars
Shugao Ma, Tomas Simon, Jason Saragih +4
Telecommunication with photorealistic avatars in virtual or augmented reality is a promising path for achieving authentic face-to-face communication in 3D over remote physical dist…
SimPoE: Simulated Character Control for 3D Human Pose Estimation
Ye Yuan, Shih-En Wei, Tomas Simon +2
Accurate estimation of 3D human motion from monocular video requires modeling both kinematics (body motion without physical forces) and dynamics (motion with physical forces). To d…
High-fidelity Face Tracking for AR/VR via Deep Lighting Adaptation
Lele Chen, Chen Cao, Fernando De la Torre +3
3D video avatars can empower virtual communications by providing compression, privacy, entertainment, and a sense of presence in AR/VR. Best 3D photo-realistic AR/VR avatars driven…
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…