Traditional supervised visual learning simply asks annotators “what” label an image should have. We propose an approach for image classification problems requiring subjective...
We address the problem of learning view-invariant 3D models of human motion from motion capture data, in order to recognize human actions from a monocular video sequence with arbi...
We present a wide-baseline image matching approach
based on line segments. Line segments are clustered into
local groups according to spatial proximity. Each group is
treated as...
This paper presents a camera tracking system for the spatial stabilization of Augmented Reality (AR) media. Our approach integrates both artificial landmarks (fiducials) and natur...
Many computer vision tasks can be formulated as labeling problems. The desired solution is often a spatially smooth labeling where label transitions are aligned with color edges o...
Christoph Rhemann, Asmaa Hosni, Michael Bleyer, Ca...