We present a practical algorithm that provably achieves the global optimum for a class of bilinear programs commonly arising in computer vision applications. Our approach relies o...
Most existing subspace analysis-based tracking algorithms utilize a flattened vector to represent a target, resulting in a high dimensional data learning problem. Recently, subspa...
Xi Li, Weiming Hu, Zhongfei Zhang, Xiaoqin Zhang, ...
To what extent can three-dimensional shape and radiance be inferred from a collection of images? Can the two be estimated separately while retaining optimality? How should the opt...
Abstract. Building visual recognition models that adapt across different domains is a challenging task for computer vision. While feature-learning machines in the form of hierarchi...
Amr Ahmed, Kai Yu, Wei Xu, Yihong Gong, Eric P. Xi...
We consider the problem of image comparison in order to match smooth surfaces under varying illumination. In a smooth surface nearby surface normals are highly correlated. We model...
Margarita Osadchy, Michael Lindenbaum, David W. Ja...