In this paper, we propose a Bayesian approach to image hallucination. Given a generic low resolution image, we hallucinate a high resolution image using a set of training images. ...
Jian Sun, Nanning Zheng, Hai Tao, Heung-Yeung Shum
We present a new approach, called local discriminant embedding (LDE), to manifold learning and pattern classification. In our framework, the neighbor and class relations of data a...
We describe a novel technique for identifying semantically equivalent parts in images belonging to the same object class, (e.g. eyes, license plates, aircraft wings etc.). The vis...
We consider the problem of calibrating a highly generic imaging model, that consists of a non-parametric association of a projection ray in 3D to every pixel in an image. Previous...
Srikumar Ramalingam, Peter F. Sturm, Suresh K. Lod...
We develop an algorithm for finding and kinematically tracking multiple people in long sequences. Our basic assumption is that people tend to take on certain canonical poses, even...