His primary scientific interests are in Artificial intelligence, Computer vision, Motion capture, Pose and RGB color model. His work carried out in the field of Artificial intelligence brings together such families of science as Kinematics and Graphics. Computer vision is closely attributed to Computer graphics in his study.
His research in Motion capture intersects with topics in Motion estimation, Ground truth, Computing Methodologies and State. His Pose research is multidisciplinary, relying on both Convolutional neural network and Robustness. His RGB color model research incorporates elements of Segmentation and Computer graphics.
Christian Theobalt focuses on Artificial intelligence, Computer vision, Motion capture, Pose and Computer graphics. His Artificial intelligence study often links to related topics such as Graphics. Computer vision is closely attributed to Kinematics in his research.
His research investigates the link between Motion capture and topics such as Surface that cross with problems in Algorithm. The various areas that Christian Theobalt examines in his Pose study include Ground truth, Convolutional neural network and Robustness. His research investigates the connection between Computer graphics and topics such as Video tracking that intersect with issues in Video capture.
His primary areas of study are Artificial intelligence, Computer vision, Monocular, Graphics and Face. Artificial intelligence and Pattern recognition are frequently intertwined in his study. His research links Convolutional neural network with Computer vision.
His research in Monocular focuses on subjects like Robustness, which are connected to Algorithm. His Graphics research is multidisciplinary, incorporating elements of Computer graphics and View synthesis. Christian Theobalt interconnects Facial expression and Image formation in the investigation of issues within Face.
Christian Theobalt mostly deals with Artificial intelligence, Computer vision, Graphics, Rendering and Computer graphics. His Artificial intelligence study frequently draws connections between related disciplines such as Pattern recognition. Monocular and Motion capture are the core of his Computer vision study.
Christian Theobalt has included themes like Embedding and View synthesis in his Graphics study. His studies in Rendering integrate themes in fields like Virtual reality and Texture mapping. His Computer graphics study incorporates themes from Surface and Face.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Free-viewpoint video of human actors
Joel Carranza;Christian Theobalt;Marcus A. Magnor;Hans-Peter Seidel.
international conference on computer graphics and interactive techniques (2003)
Performance capture from sparse multi-view video
Edilson de Aguiar;Carsten Stoll;Christian Theobalt;Naveed Ahmed.
international conference on computer graphics and interactive techniques (2008)
Face2Face: Real-Time Face Capture and Reenactment of RGB Videos
Justus Thies;Michael Zollhofer;Marc Stamminger;Christian Theobalt.
computer vision and pattern recognition (2016)
VNect: real-time 3D human pose estimation with a single RGB camera
Dushyant Mehta;Srinath Sridhar;Oleksandr Sotnychenko;Helge Rhodin.
international conference on computer graphics and interactive techniques (2017)
Motion capture using joint skeleton tracking and surface estimation
Juergen Gall;Carsten Stoll;Edilson de Aguiar;Christian Theobalt.
computer vision and pattern recognition (2009)
3D shape scanning with a time-of-flight camera
Yan Cui;Sebastian Schuon;Derek Chan;Sebastian Thrun.
computer vision and pattern recognition (2010)
A Data-Driven Approach for Real-Time Full Body Pose Reconstruction from a Depth Camera.
Andreas Baak;Meinard Muller;Gaurav Bharaj;Hans-Peter Seidel.
Consumer Depth Cameras for Computer Vision (2013)
BundleFusion: real-time globally consistent 3D reconstruction using on-the-fly surface re-integration
Angela Dai;Matthias Nießner;Michael Zollhöfer;Shahram Izadi.
ACM Transactions on Graphics (2017)
Real-time non-rigid reconstruction using an RGB-D camera
Michael Zollhöfer;Matthias Nießner;Shahram Izadi;Christoph Rehmann.
international conference on computer graphics and interactive techniques (2014)
A Noise‐aware Filter for Real‐time Depth Upsampling
Derek Chan;Hylke Buisman;Christian Theobalt;Sebastian Thrun.
Workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications - M2SFA2 2008 (2008)
Profile was last updated on December 6th, 2021.
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