This paper describes a statistically motivated framework for performing real-time dialogue state updates and policy learning in a spoken dialogue system. The framework is based on...
High-level generative models provide elegant descriptions of videos and are commonly used as the inference framework in many unsupervised motion segmentation schemes. However, app...
Though it has cost great research efforts for decades, object recognition is still a challenging problem. Traditional methods based on machine learning or computer vision are stil...
Xin-Jing Wang, Ming Liu, Lei Zhang, Yi Li, Wei-Yin...
In this paper, we propose a new stereo matching method using the population-based Markov Chain Monte Carlo (Pop-MCMC), which belongs to the sampling-based methods. Since the previo...
Wonsik Kim (Seoul National University), Joonyoung ...
Classifying pictures into one of several semantic categories is a classical image understanding problem. In this paper, we present a stratified approach to both binary (outdoor-in...