Depth ordering is instrumental for understanding the 3D geometry of an image. We as humans are surprisingly good ordering even with abstract 2D line drawings. In this paper we pro...
Zhaoyin Jia, Andrew C. Gallagher, Yao-Jen Chang, T...
Many problems in computer vision can be modeled using
conditional Markov random fields (CRF). Since finding
the maximum a posteriori (MAP) solution in such models
is NP-hard, mu...
Stephen Gould (Stanford University), Fernando Amat...
The accurate localization of facial features plays a fundamental
role in any face recognition pipeline. Constrained
local models (CLM) provide an effective approach to localizati...
This paper presents a novel spatio-temporal Markov random field (MRF) for video denoising. Two main issues are addressed in this paper, namely, the estimation of noise model and t...
This paper presents an approach for including 3D prior models into a factorization framework for structure from motion. The proposed method computes a closed-form affine fit which...