In this paper we propose a method for matching articulated shapes represented as large sets of 3D points by aligning the corresponding embedded clouds generated by locally linear ...
Diana Mateus, Fabio Cuzzolin, Radu Horaud, Edmond ...
In this paper, we propose a novel metric learning method based on regularized moving least squares. Unlike most previous metric learning methods which learn a global Mahalanobis d...
In this paper, a new approach for object detection and pose estimation is introduced. The contribution consists in the conception of entities permitting stable detection and relia...
Stefan Hinterstoisser, Selim Benhimane, Nassir Nav...
We present a novel approach to reconstruction based superresolution that explicitly models the detector's pixel layout. Pixels in our model can vary in shape and size, and th...
3?D shape recovery of non-rigid surfaces from 3?D to 2?D correspondences is an under-constrained problem that requires prior knowledge of the possible deformations. State-of-the-a...