Embedding images into a low dimensional space has a wide range of applications: visualization, clustering, and pre-processing for supervised learning. Traditional dimension reduct...
—We propose an approach for improving object recognition and localization using spatial kernels together with instance embedding. Our approach treats each image as a bag of insta...
Registration of 3D surfaces is a critical step for shape analysis. Recent studies show that spectral representations based on intrinsic pairwise geodesic distances between points ...
Xiuwen Liu, Arturo Donate, Matthew Jemison, Washin...
The locally linear embedding (LLE) algorithm is considered as a powerful method for the problem of nonlinear dimensionality reduction. In this paper, first, a new method called cl...
Graphs are powerful data structures that have many attractive properties for object representation. However, some basic operations are difficult to define and implement, for ins...
Miquel Ferrer, Ernest Valveny, Francesc Serratosa,...