Abstract Partially observable Markov decision processes (POMDPs) are a principled mathematical framework for planning under uncertainty, a crucial capability for reliable operation...
Hanna Kurniawati, Yanzhu Du, David Hsu, Wee Sun Le...
Manifold bootstrapping is a new method for data-driven modeling of real-world, spatially-varying reflectance, based on the idea that reflectance over a given material sample forms...
Yue Dong, Jiaping Wang, Xin Tong, John Snyder, Yan...
Most of the meshes coming from a variety of source are over sampled and exhibit highly irregular connectivity that prevent efficient wavelet analysis. Remeshing comes as a solutio...
Alexandre Gouaillard, Arnaud Gelas, Eric Boix, R&e...
We consider the problem of automatically learning color enhancements from a small set of sample color pairs, and describing the enhancement by a three-dimensional look-uptable tha...
This article proposes a new statistical model for fast 3D articulated body tracking, similar to the loose-limbed model, but where inter-frame coherence is taken into account by us...