What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Geometry
- Computer vision
His primary areas of investigation include Artificial intelligence, Algorithm, Computer vision, Animation and Geometry.
His Artificial intelligence study frequently links to other fields, such as Computer graphics.
His work deals with themes such as Cluster analysis, Surface reconstruction, Mathematical optimization, Euclidean geometry and Shape analysis, which intersect with Algorithm.
His studies deal with areas such as Computer facial animation, Facial expression and Robustness as well as Computer vision.
His Geometry research includes elements of Hardware acceleration, Representation and Moving least squares.
His studies in Point integrate themes in fields like Point cloud and Fourier transform.
His most cited work include:
- Efficient simplification of point-sampled surfaces (605 citations)
- Realtime performance-based facial animation (460 citations)
- Partial and approximate symmetry detection for 3D geometry (439 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Artificial intelligence, Computer vision, Computer graphics, Algorithm and Surface.
His research integrates issues of Set and Pattern recognition in his study of Artificial intelligence.
The study incorporates disciplines such as Computer facial animation, Process and Facial expression in addition to Computer vision.
His Geometric modeling research extends to the thematically linked field of Computer graphics.
Much of his study explores Algorithm relationship to Mathematical optimization.
His study in Surface is interdisciplinary in nature, drawing from both Point, Engineering drawing and Optics.
He most often published in these fields:
- Artificial intelligence (30.20%)
- Computer vision (25.50%)
- Computer graphics (15.44%)
What were the highlights of his more recent work (between 2016-2021)?
- Surface (12.75%)
- Topology (8.72%)
- Composite material (2.01%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Surface, Topology, Composite material, Mechanical metamaterial and Encoding.
His Surface research is multidisciplinary, incorporating perspectives in Optics, Projection, Ray, Caustic and Element.
The concepts of his Topology study are interwoven with issues in Smart material and Regular polygon.
His work on Brick as part of general Composite material study is frequently connected to Bond, Flock, Lamella and Computational design, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
Mark Pauly combines subjects such as State and Bistability with his study of Mechanical metamaterial.
His Encoding study integrates concerns from other disciplines, such as Design paradigm, Linkage and Scale factor.
Between 2016 and 2021, his most popular works were:
- Online generative model personalization for hand tracking (65 citations)
- Phace: physics-based face modeling and animation (41 citations)
- Low-Dimensionality Calibration through Local Anisotropic Scaling for Robust Hand Model Personalization (34 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Geometry
- Optics
Artificial intelligence, Match moving, Computer vision, Programming language and Theoretical computer science are his primary areas of study.
His work on Curse of dimensionality as part of general Artificial intelligence study is frequently linked to Generative model, bridging the gap between disciplines.
His Match moving study combines topics from a wide range of disciplines, such as Algorithm, Degrees of freedom, Robustness and Pipeline.
The Motion capture research Mark Pauly does as part of his general Computer vision study is frequently linked to other disciplines of science, such as Personalization, therefore creating a link between diverse domains of science.
His work carried out in the field of Programming language brings together such families of science as Transformation, Variety, Procedural modeling and Rule-based machine translation.
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