Unsupervised learning methods often involve summarizing the data using a small number of parameters. In certain domains, only a small subset of the available data is relevant for ...
This paper presents a stochastic iteration algorithm solving the global illumination problem, where the random sampling is governed by classical importance sampling and also by th...
This paper revisits the problem of source-channel coding for error-resilient video streaming. We propose a new method to enable adaptive redundancy in the bitstream: fine-grain r...
In this paper, we describe a prior-based vanishing point estimation method through global perspective structure matching (GPSM). In contrast to the traditional approaches which re...
Qi Wu, Wende Zhang, Tsuhan Chen, B. V. K. Vijaya K...
In this paper, we present an analytical method for computing the globally optimal estimates of orthogonal vanishing points in a “Manhattan world” with a calibrated camera. We ...