In this paper, we present a new Adaptive Scale Kernel Consensus (ASKC) robust estimator as a generalization of the popular and state-of-the-art robust estimators such as RANSAC (R...
This paper proposes a new Bayesian framework for solving the matting problem, i.e. extracting a foreground element from a background image by estimating an opacity for each pixel ...
Yung-Yu Chuang, Brian Curless, David Salesin, Rich...
Abstract. In this paper, we investigate brain hallucination, or generating a high resolution brain image from an input low-resolution image, with the help of another high resolutio...
In practice, understanding the spatial relationships between the surfaces of an object, can significantly improve the performance of object recognition systems. In this paper we p...
This paper introduces a hierarchical approach for multicomponent tracking, where the object-to-be-tracked is modeled as a group of spatial related parts. We propose to use a robus...