3 citations · 4 across the 3 of their papers we have counts for
6 papers
Manifold Sampling for Differentiable Uncertainty in Radiance Fields
Linjie Lyu, Ayush Tewari, Marc Habermann +4
Radiance fields are powerful and, hence, popular models for representing the appearance of complex scenes. Yet, constructing them based on image observations gives rise to ambiguit…
Dynamic Neural Radiance Fields for Monocular 4D Facial Avatar Reconstruction
Guy Gafni, Justus Thies, Michael Zollhöfer +1
We present dynamic neural radiance fields for modeling the appearance and dynamics of a human face. Digitally modeling and reconstructing a talking human is a key building-block fo…
Neural Deformation Graphs for Globally-consistent Non-rigid Reconstruction
Aljaž Božič, Pablo Palafox, Michael Zollhöfer +3
We introduce Neural Deformation Graphs for globally-consistent deformation tracking and 3D reconstruction of non-rigid objects. Specifically, we implicitly model a deformation grap…
Neural Non-Rigid Tracking
Aljaž Božič, Pablo Palafox, Michael Zollhöfer +3
We introduce a novel, end-to-end learnable, differentiable non-rigid tracker that enables state-of-the-art non-rigid reconstruction by a learned robust optimization. Given two inpu…
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…
Commodity RGB-D Sensors: Data Acquisition
Michael Zollhöfer
Over the past ten years we have seen a democratization of range sensing technology. While previously range sensors have been highly expensive and only accessible to a few domain ex…