We study unsupervised learning of occluding objects in images of visual scenes. The derived learning algorithm is based on a probabilistic generative model which parameterizes obj...
In this paper, we investigate what can be inferred from several silhouette probability maps, in multi-camera environments. To this aim, we propose a new framework for multi-view s...
in Proc. IEEE Int’l Conf. on Computer Vision (ICCV), October, 2007 Traditional Bayesian restoration methods depend heavily on the accuracy of underlying generative models. For t...
Yunqiang Chen, Lin Cheng, Tong Fang, Rainer Raupac...
In this paper we present a method to relight human faces in real time, using consumer-grade graphics cards even with limited 3D capabilities. We show how to render faces using a c...
In Deep Sub-Micron (DSM) designs, performance will depend critically on the latency of long wires. We propose a new synthesis methodology for synchronous systems that makes the de...
Luca P. Carloni, Kenneth L. McMillan, Alexander Sa...