Object pose recovery has gained increasing attention in the computer vision field as it has
become an important problem in rapidly evolving technological areas related to autonomous …

We present a novel approach to category-level 6D object pose and size estimation. To
tackle intra-class shape variations, we learn canonical shape space (CASS), a unified …

In this paper we examine the effects of using object poses as guidance to learning robust
features for 3D object pose estimation. Previous works have focused on learning feature …

A large number of studies analyse object detection and pose estimation at visual level in 2D,
discussing the effects of challenges such as occlusion, clutter, texture, etc., on the …

Intra-class variations, distribution shifts among source and target domains are the major
challenges of category-level tasks. In this study, we address category-level full 6D object …

Object detection from RGB images is a long-standing problem in image processing and
computer vision. It has applications in various domains including robotics, surveillance …

3-D pose estimation for texture-less objects remains a challenging problem. Previous works
either focus on a template matching method to find the nearest template as a candidate, or …

Interest in estimating the 6D pose, ie 3D locations and rotations, of an object of interest has
emerged since its promising applications in fields such as robotics and augmented reality …

Shell parts which have symmetric structure, even surface and flat color are common in
industrial manufacturing applications. Moreover, the inner and outer surface of them are of …

State-of-the-art techniques for 6D object pose recovery depend on occlusion-free point
clouds to accurately register objects in 3D space. To deal with this shortcoming, we …