C
Christian Theobalt
Researcher at Max Planck Society
Publications - 508
Citations - 34680
Christian Theobalt is an academic researcher from Max Planck Society. The author has contributed to research in topics: Motion capture & Computer science. The author has an hindex of 89, co-authored 450 publications receiving 25487 citations. Previous affiliations of Christian Theobalt include Stanford University & Facebook.
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Model-based analysis of multi-video data
Marcus Magnor,Christian Theobalt +1 more
TL;DR: In this article, a method to analyze multiple synchronized video streams by making use of a parameterized geometry model of the recorded object is presented, which is able to capture the time-varying 3D pose of the object automatically and robustly.
Posted Content
EventHands: Real-Time Neural 3D Hand Reconstruction from an Event Stream
Viktor Rudnev,Vladislav Golyanik,Jiayi Wang,Hans-Peter Seidel,Franziska Mueller,Mohamed Elgharib,Christian Theobalt +6 more
TL;DR: This work addresses 3D hand pose estimation from monocular videos for the first time using a single event camera, i.e., an asynchronous vision sensor reacting on brightness changes, and designs a new neural approach which accepts a new event stream representation suitable for learning, trained on newly-generated synthetic event streams.
Posted Content
HumanGAN: A Generative Model of Humans Images
TL;DR: Zhang et al. as discussed by the authors proposed a generative model for images of dressed humans offering control over pose, local body part appearance and garment style, which is the first method to solve various aspects of human image generation such as global appearance sampling, pose transfer, parts and garment transfer, and parts sampling jointly in a unified framework.
Fast Tracking of Hand and Finger Articulations Using a Single Depth Camera
TL;DR: This paper frames pose estimation as an optimization problem in depth using a new objective function based on a collection of Gaussian functions, focusing particularly on robust tracking of finger articulations, and shows that the method achieves competitive accuracy.