In this paper we present a generative model and learning procedure for unsupervised video clustering into scenes. The work addresses two important problems: realistic modeling of ...
Nemanja Petrovic, Aleksandar Ivanovic, Nebojsa Joj...
In this paper we present a hierarchical, learning-based approach for automatic and accurate liver segmentation from 3D CT volumes. We target CT volumes that come from largely dive...
Haibin Ling, Shaohua Kevin Zhou, Yefeng Zheng, Bog...
Learning-based superresolution (SR) are popular SR techniques that use application dependent priors to infer the missing details in low resolution images (LRIs). However, their pe...
Particle filters are used for hidden state estimation with nonlinear dynamical systems. The inference of 3-d human motion is a natural application, given the nonlinear dynamics of...
This work takes place in the context of hierarchical stochastic models for the resolution of discrete inverse problems from low level vision. Some of these models lie on the nodes...