In recent years the Markov Random Field (MRF) has
become the de facto probabilistic model for low-level vision
applications. However, in a maximum a posteriori
(MAP) framework, ...
Oliver J. Woodford, Carsten Rother, Vladimir Kolmo...
This paper describes a discriminatively trained, multiscale, deformable part model for object detection. Our system achieves a two-fold improvement in average precision over the b...
Pedro F. Felzenszwalb, David A. McAllester, Deva R...
Geometric reconstruction problems in computer vision are often solved by minimizing a cost function that combines the reprojection errors in the 2D images. In this paper, we show t...
We prove that the set of all Lambertian reflectance functions (the mapping from surface normals to intensities) obtained with arbitrary distant light sources lies close to a 9D lin...
This paper presents a new approach for virtual view synthesis that does not require any information of scene geometry. Our approach first generates multiple virtual views at the s...