This tutorial presents a hands-on view of the field of multi-view stereo with a focus on
practical algorithms. Multi-view stereo algorithms are able to construct highly detailed 3D …

Optimization methods are at the core of many problems in signal/image processing,
computer vision, and machine learning. For a long time, it has been recognized that looking …

Optical flow estimation is one of the oldest and still most active research domains in
computer vision. In 35 years, many methodological concepts have been introduced and …

We present a new approach for predicting program properties from massive codebases
(aka" Big Code"). Our approach first learns a probabilistic model from existing data and then …

Image segmentation refers to the process to divide an image into meaningful non-
overlapping regions according to human perception, which has become a classic topic since …

We describe a method to automatically detect contours, ie lines along which the surface
orientation sharply changes, in large-scale outdoor point clouds. Contours are important …

We introduce a new compression scheme for high-dimensional vectors that approximates
the vectors using sums of M codewords coming from M different codebooks. We show that …

During the last decades, the research community of medical imaging has witnessed
continuous advances in image registration methods, which pushed the limits of the state-of …

In this paper, we present a comprehensive survey of Markov Random Fields (MRFs) in
computer vision and image understanding, with respect to the modeling, the inference and …

Lung image registration can effectively describe the relative motion of lung tissues, thereby
helping to solve series problems in clinical applications. Since the lungs are soft and fairly …