What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Computer graphics
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.
His most cited work include:
- Face2Face: Real-Time Face Capture and Reenactment of RGB Videos (682 citations)
- VNect: real-time 3D human pose estimation with a single RGB camera (572 citations)
- Free-viewpoint video of human actors (501 citations)
What are the main themes of his work throughout his whole career to date?
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.
He most often published in these fields:
- Artificial intelligence (77.51%)
- Computer vision (67.46%)
- Motion capture (21.77%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial intelligence (77.51%)
- Computer vision (67.46%)
- Monocular (14.59%)
In recent papers he was focusing on the following fields of study:
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.
Between 2019 and 2021, his most popular works were:
- State of the Art on Neural Rendering (54 citations)
- Neural Sparse Voxel Fields (50 citations)
- StyleRig: Rigging StyleGAN for 3D Control Over Portrait Images (48 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Algorithm
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.
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