Our objective is transfer training of a discriminatively trained object category detector, in order to reduce the number of training images required. To this end we propose three ...
We consider the problem of predicting a sequence of real-valued multivariate states from a given measurement sequence. Its typical application in computer vision is the task of mo...
We introduce a framework for computing statistically optimal estimates of geometric reconstruction problems. While traditional algorithms often suffer from either local minima or ...
We present a powerful framework for 3D-texture-based rendering of multiple arbitrarily intersecting volumetric datasets. Each volume is represented by a multi-resolution octree-bas...
John Plate, Thorsten Holtkaemper, Bernd Froehlic...
Conditional Random Field models have proved effective for several low-level computer vision problems. Inference in these models involves solving a combinatorial optimization probl...