This paper focuses on hallucinating a facial shape from a low-resolution 3D facial shape. Firstly, we give a constrained conformal embedding of 3D shape in R2 , which establishes ...
Recently, manifold learning has been widely exploited in pattern recognition, data analysis, and machine learning. This paper presents a novel framework, called Riemannian manifold...
Abstract. In this paper, we show how to efficiently and effectively extract a rich class of low-rank textures in a 3D scene from 2D images despite significant distortion and warpin...
Multi-tensor models provide information about the fiber bundles underlying characteristics and are of great interest for clinical applications. In this work we propose both a nov...
Most existing methods of semi-supervised clustering introduce supervision from outside, e.g., manually label some data samples or introduce constrains into clustering results. Thi...