This work is concerned with the structure of bilinear minimization problems arising in recovering subsampled and modulated images in parallel magnetic resonance imaging. By consid...
Conditional Random Field models have proved effective for several low-level computer vision problems. Inference in these models involves solving a combinatorial optimization probl...
We present a novel representation and rendering method for free-viewpoint video of human characters based on multiple input video streams. The basic idea is to approximate the art...
Marcel Germann, Alexander Hornung, Richard Keiser,...
Abstract. We propose a non-standard neural network called TPNN which offers the direct mapping from a peptide sequence to a property of interest in order to model the quantitative ...
We consider the structure from motion problem for a previously introduced, highly general imaging model, where cameras are modeled as possibly unconstrained sets of projection ray...