Image matching has a history of more than 50 years, with the first experiments performed
with analogue procedures for cartographic and map** purposes. The recent integration of …

With the advent of convolutional neural networks, stereo matching algorithms have recently
gained tremendous progress. However, it remains a great challenge to accurately extract …

Stereo depth estimation relies on optimal correspondence matching between pixels on
epipolar lines in the left and right images to infer depth. In this work, we revisit the problem …

Salient object detection has been attracting a lot of interest, and recently various heuristic
computational models have been designed. In this paper, we regard saliency map …

Humans perceive the three-dimensional structure of the world with apparent ease. However,
despite all of the recent advances in computer vision research, the dream of having a …

Light Field (LF) depth estimation is an important research direction in the area of computer
vision and computational photography, which aims to infer the depth information of different …

Stereo matching is one of the most active research areas in computer vision. While a large
number of algorithms for stereo correspondence have been developed, relatively little work …

Many tasks in computer vision involve assigning a label (such as disparity) to every pixel. A
common constraint is that the labels should vary smoothly almost everywhere while …

This paper describes the semiglobal matching (SGM) stereo method. It uses a pixelwise,
mutual information (Ml)-based matching cost for compensating radiometric differences of …

This paper considers the objectives of accurate stereo matching, especially at object
boundaries, robustness against recording or illumination changes and efficiency of the …