What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
Gerard Pons-Moll spends much of his time researching Artificial intelligence, Computer vision, Pose, Motion capture and Motion.
Gerard Pons-Moll brings together Artificial intelligence and Clothing to produce work in his papers.
His studies examine the connections between Computer vision and genetics, as well as such issues in Animation, with regards to Visual hull and Silhouette.
Gerard Pons-Moll combines topics linked to Computer graphics with his work on Motion.
His RGB color model research is multidisciplinary, incorporating perspectives in Face and Gesture.
His Solid modeling study combines topics from a wide range of disciplines, such as Representation, Parameterized complexity, Deep learning, Iterative reconstruction and Pattern recognition.
His most cited work include:
- SMPL: a skinned multi-person linear model (896 citations)
- Neural Body Fitting: Unifying Deep Learning and Model Based Human Pose and Shape Estimation (260 citations)
- Dyna: a model of dynamic human shape in motion (231 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Artificial intelligence, Computer vision, Pose, Motion capture and Polygon mesh.
Gerard Pons-Moll merges many fields, such as Artificial intelligence and Clothing, in his writings.
The study incorporates disciplines such as Artificial neural network and Representation in addition to Computer vision.
His studies in Pose integrate themes in fields like Perspective and Machine learning, Convolutional neural network, Pattern recognition.
He focuses mostly in the field of Motion capture, narrowing it down to topics relating to Retargeting and, in certain cases, Single view.
His work deals with themes such as Animation, Point cloud, Graphics, Algorithm and Rendering, which intersect with Polygon mesh.
He most often published in these fields:
- Artificial intelligence (84.07%)
- Computer vision (65.49%)
- Pose (23.01%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial intelligence (84.07%)
- Computer vision (65.49%)
- Algorithm (10.62%)
In recent papers he was focusing on the following fields of study:
Gerard Pons-Moll mostly deals with Artificial intelligence, Computer vision, Algorithm, Polygon mesh and Code.
He performs multidisciplinary study on Artificial intelligence and Clothing in his works.
His Computer vision research includes themes of Range and Deep learning.
The concepts of his Algorithm study are interwoven with issues in Point cloud and Distance transform.
His Polygon mesh study which covers Graphics that intersects with Shape approximation and 3d tracking.
His Pose research is multidisciplinary, relying on both Ground truth, Tracking, Perspective and Motion capture.
Between 2019 and 2021, his most popular works were:
- Implicit Functions in Feature Space for 3D Shape Reconstruction and Completion (67 citations)
- Learning to Dress 3D People in Generative Clothing (41 citations)
- XNect: real-time multi-person 3D motion capture with a single RGB camera (38 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Algorithm
The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Monocular, Implicit function and Polygon mesh.
His Artificial intelligence study frequently links to related topics such as Contrast.
In the field of Computer vision, his study on Rendering overlaps with subjects such as Radiance.
His Monocular research integrates issues from Pose and Motion capture.
His research in Pose intersects with topics in RGB color model, Convolutional neural network and Range.
His studies deal with areas such as Shape approximation and Representation as well as Polygon mesh.
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