Reinforcement learning (RL) can be impractical for many high dimensional problems because of the computational cost of doing stochastic search in large state spaces. We propose a ...
Object-space silhouette extraction is an important problem in fields ranging from non-photorealistic computer graphics to medical robotics. We present an efficient silhouette extr...
We introduce a volumetric space-time technique for the reconstruction of moving and deforming objects from point data. The output of our method is a four-dimensional space-time so...
Andrei Sharf, Dan A. Alcantara, Thomas Lewiner, Ch...
We present a simple but powerful algorithm for optimizing the usage of hardware occlusion queries in arbitrary complex scenes. Our method minimizes the number of issued queries an...
We examine the problem of large scale nearest neighbor search in high dimensional spaces and propose a new approach based on the close relationship between nearest neighbor search...