112 citations · 632 across the 28 of their papers we have counts for
5 papers · 1 filter
IMU2Face: Real-time Gesture-driven Facial Reenactment
Justus Thies, Michael Zollhöfer, Matthias Nießner
We present IMU2Face, a gesture-driven facial reenactment system. To this end, we combine recent advances in facial motion capture and inertial measurement units (IMUs) to control t…
Self-supervised Multi-level Face Model Learning for Monocular Reconstruction at over 250 Hz
Ayush Tewari, Michael Zollhöfer, Pablo Garrido +4
The reconstruction of dense 3D models of face geometry and appearance from a single image is highly challenging and ill-posed. To constrain the problem, many approaches rely on str…
MonoPerfCap: Human Performance Capture from Monocular Video
Weipeng Xu, Avishek Chatterjee, Michael Zollhöfer +4
We present the first marker-less approach for temporally coherent 3D performance capture of a human with general clothing from monocular video. Our approach reconstructs articulate…
InverseFaceNet: Deep Monocular Inverse Face Rendering
Hyeongwoo Kim, Michael Zollhöfer, Ayush Tewari +3
We introduce InverseFaceNet, a deep convolutional inverse rendering framework for faces that jointly estimates facial pose, shape, expression, reflectance and illumination from a s…
MoFA: Model-based Deep Convolutional Face Autoencoder for Unsupervised Monocular Reconstruction
Ayush Tewari, Michael Zollhöfer, Hyeongwoo Kim +4
In this work we propose a novel model-based deep convolutional autoencoder that addresses the highly challenging problem of reconstructing a 3D human face from a single in-the-wild…