We introduce an approach to accurately detect and segment partially occluded objects in various viewpoints and scales. Our main contribution is a novel framework for combining obj...
This paper presents a novel method for quickly filtering range data points to make object recognition in large 3D data sets feasible. The general approach, called "3D cueing,...
Abstract. This paper presents a new approach to the problem of simultaneous location and segmentation of object in images. The main emphasis is done on the information provided by ...
This chapter proposes a representation of rigid three-dimensional (3D) objects in terms of local affine-invariant descriptors of their images and the spatial relationships between ...
Fred Rothganger, Svetlana Lazebnik, Cordelia Schmi...
3D object detection and importance regression/ranking are at the core for semantically interpreting 3D medical images of computer aided diagnosis (CAD). In this paper, we propose ...
Le Lu, Jinbo Bi, Matthias Wolf, Marcos Salganicoff