Abstract. We present a technique for learning the parameters of a continuousstate Markov random field (MRF) model of optical flow, by minimizing the training loss for a set of grou...
We introduce a generative model of dense flow fields within a layered representation of 3-dimensional scenes. Using probabilistic inference and learning techniques (namely, varia...
We describe an algorithm for automatically finding correspondences from face video sequences. This method is useful to many applications such as face tracking, face modeling and ...
Hui Fang, Nicholas Costen, David Cristinacce, John...
We introduce the concept of complementarity between data and smoothness term in modern variational optic flow methods. First we design a sophisticated data term that incorporates ...
Reconstruction-based super-resolution from motion video has been an active area of study in computer vision and video analysis. Image alignment is a key component of super-resoluti...