The Center for Visual Computing – established in 2011 – lies on the intersection of mathematics and computer science seeking mathematical models and their computational solutions towards automatic structuring, interpretation and understanding of massive (visual) data with emphasis on machine learning, optimization, computer vision and biomedical image analysis.
COMPUTER VISION & 3D MODELING
Image reconstruction, boundary detection, model-free and model-based segmentation, optical flow estimation and tracking, image parsing, object recognition, and large scale grammar-based 3D modeling.
MACHINE LEARNING & OPTIMIZATION
Probabilistic graphical models, self-paced learning, multiple-instance learning, structure output regression, sparsity, kernel methods, multi-task/online/transfer learning.
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BIOMEDICAL IMAGE ANALYSIS (INRIA GALEN TEAM)
Compressed sensing and reconstruction, tumor detection, organ segmentation, image deformable registration and fusion, longitudinal organ modeling, computational anatomy, population studies, brain understanding.