Boosting is a remarkably simple and flexible classification algorithm with widespread applications in computer vision. However, the application of boosting to nonEuclidean, infini...
In this paper, we overcome a major drawback of the level set framework: the lack of point correspondences. We maintain explicit backward correspondences from the evolving interfac...
Abstract. Shape retrieval/matching is a very important topic in computer vision. The recent progress in this domain has been mostly driven by designing smart features for providing...
Xingwei Yang, Xiang Bai, Longin Jan Latecki, Zhuow...
Tracking the 3-D pose of an object needs correspondences between 2-D features in the image and their 3-D counterparts in the object model. A large variety of such features has been...
Thomas Brox, Bodo Rosenhahn, Daniel Cremers, Hans-...
The performance of many computer vision and machine learning algorithms critically depends on the quality of the similarity measure defined over the feature space. Previous works...