22 citations · 27 across the 3 of their papers we have counts for
9 papers
iSDF: Real-Time Neural Signed Distance Fields for Robot Perception
Joseph Ortiz, Alexander Clegg, Jing Dong +4
We present iSDF, a continual learning system for real-time signed distance field (SDF) reconstruction. Given a stream of posed depth images from a moving camera, it trains a random…
COAP: Compositional Articulated Occupancy of People
Marko Mihajlovic, Shunsuke Saito, Aayush Bansal +2
We present a novel neural implicit representation for articulated human bodies. Compared to explicit template meshes, neural implicit body representations provide an efficient mech…
Mutual Scene Synthesis for Mixed Reality Telepresence
Mohammad Keshavarzi, Michael Zollhoefer, Allen Y. Yang +2
Remote telepresence via next-generation mixed reality platforms can provide higher levels of immersion for computer-mediated communications, allowing participants to engage in a wi…
Real-time Deep Dynamic Characters
Marc Habermann, Lingjie Liu, Weipeng Xu +3
We propose a deep videorealistic 3D human character model displaying highly realistic shape, motion, and dynamic appearance learned in a new weakly supervised way from multi-view i…
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…
A-NeRF: Articulated Neural Radiance Fields for Learning Human Shape, Appearance, and Pose
Shih-Yang Su, Frank Yu, Michael Zollhoefer +1
While deep learning reshaped the classical motion capture pipeline with feed-forward networks, generative models are required to recover fine alignment via iterative refinement. Un…