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...
This paper presents a new technique to segment objects of interest from cluttered background with varying edge densities and illumination conditions from gray scale imagery. An op...
M. Raffay Hamid, Aijaz Baloch, Ahmed Bilal, Nauman...
This paper reviews a class of methods to perform causal inference in the framework of a structural vector autoregressive model. We consider three different settings. In the first ...
We combine Bayesian online change point detection with Gaussian processes to create a nonparametric time series model which can handle change points. The model can be used to loca...
We propose a method for estimating confidence regions around shapes predicted from partial observations, given a statistical shape model. Our method relies on the estimation of the...