What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Computer graphics
His main research concerns Artificial intelligence, Computer vision, Computer graphics, Iterative reconstruction and Pixel.
Artificial intelligence is frequently linked to Sequence in his study.
His research on Computer vision frequently connects to adjacent areas such as Algorithm.
His Computer graphics study incorporates themes from 3d scanning, Parallelism, Sensor fusion and Polygon.
The study incorporates disciplines such as Image resolution, Data mining, Matching, Cluster analysis and Stereopsis in addition to Iterative reconstruction.
His Pixel research includes themes of Bayesian framework, Poisson image editing, Image stitching and Feature extraction, Pattern recognition.
His most cited work include:
- A volumetric method for building complex models from range images (2340 citations)
- A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms (1827 citations)
- Image analogies (1331 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Computer graphics, Iterative reconstruction and Rendering.
Within one scientific family, Brian Curless focuses on topics pertaining to Surface reconstruction under Artificial intelligence, and may sometimes address concerns connected to Planar.
His Computer vision study is mostly concerned with Image-based modeling and rendering, Object, Ground truth, 3D reconstruction and Image.
Brian Curless has included themes like Augmented reality and Visualization in his Computer graphics study.
The various areas that he examines in his Iterative reconstruction study include Stereopsis, Photometric stereo, Image resolution and Cluster analysis.
His research integrates issues of Feature extraction and Pattern recognition in his study of Pixel.
He most often published in these fields:
- Artificial intelligence (66.39%)
- Computer vision (63.03%)
- Computer graphics (42.86%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (66.39%)
- Computer vision (63.03%)
- Ground truth (5.88%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Artificial intelligence, Computer vision, Ground truth, Domain and Polygon mesh.
His work on Augmented reality, Image warping and Face as part of general Artificial intelligence study is frequently linked to Desk and Network on, bridging the gap between disciplines.
His Augmented reality research integrates issues from Depth map, 3D reconstruction and Computer graphics.
His Computer vision research is multidisciplinary, incorporating perspectives in Light stage and Alpha.
His research integrates issues of Linear regression and Data collection in his study of Ground truth.
His studies in Polygon mesh integrate themes in fields like Image synthesis, Animation and View synthesis, Rendering.
Between 2017 and 2021, his most popular works were:
- Soccer on Your Tabletop (63 citations)
- Photo Wake-Up: 3D Character Animation From a Single Photo (39 citations)
- Detailed 3-dimensional body shape features predict body composition, blood metabolites, and functional strength: the Shape Up! studies. (17 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Computer graphics
His primary areas of investigation include Artificial intelligence, Computer vision, Ground truth, Augmented reality and Image segmentation.
His work on Resolution as part of general Artificial intelligence study is frequently connected to Domain, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
Brian Curless performs integrative study on Computer vision and Large set.
His Ground truth study incorporates themes from Depth map, 3D reconstruction and Iterative reconstruction.
His studies deal with areas such as Character animation, Silhouette, Computer graphics and Image warping as well as Augmented reality.
Brian Curless combines Image segmentation and Bridge in his research.
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