Rushil

ALT Owing to the emerging interest in Riemannnian geometric computing, this workshop will focus on both advances in differential geometric methods for computer vision and medical imaging, as well as topics that exploit machine learning algorithms that efficiently perform inference on geometric structures from data. This workshop will serve as a welcoming forum not only to researchers in the CVPR community but also will also appeal to a broader audience in the statistical shape analysis, machine learning, statistical image analysis, applications of Riemannian geometry in computer vision, graphics, and the statistics and machine learning communities. Topics Deep learning and geometry. Riemannian methods in computer vision Statistical shape analysis Statistical analysis on manifolds Manifold-valued features and learning Machine learning on nonlinear manifolds Shape detection, tracking and retrieval Topological methods in structure analysis Functional Data Analysis