Object pose estimation is a core perception task that enables, for example, object
manipulation and scene understanding. The widely available, inexpensive, and high …

One critical challenge in 6D object pose estimation from a single RGBD image is efficient
integration of two different modalities, ie, color and depth. In this work, we tackle this problem …

Category-level 6DoF object pose estimation intends to estimate the rotation, translation, and
size of unseen objects. Many previous works use point clouds as a pre-learned shape prior …

Point cloud shape completion plays a central role in diverse 3D vision and robotics
applications. Early methods used to generate global shapes without local detail refinement …

Monocular object 6D pose estimation is a fundamental yet challenging task in computer
vision. Recently, deep learning has been proven to be capable of predicting remarkable …

Estimating the 6-D pose of an object is a vital and challenging task for robot vision systems
in industrial robotic grasping. With the wide use of 3-D cameras, the additional acquired …

Efficient and accurate estimation of objects' pose is essential in numerous practical
applications. Due to the depth data contains abundant geometric information, some existing …

Illumination harmonization is an important but challenging task that aims to achieve
illumination compatibility between the foreground and background under different …

Accurate and robust 6-DOF (6D) pose estimation from a single RGB image and depth map
(RGB-D) image is an essential task of intelligent manufacturing, such as robot assembly and …

Abstract 6D pose estimation has garnered significant attention and research. RGB images
and point clouds converted from RGB-D images provide complementary color and geometry …