This paper presents a comprehensive survey on vision-based robotic gras**. We
conclude three key tasks during vision-based robotic gras**, which are object localization …

Transformers have revolutionized vision and natural language processing with their ability to
scale with large datasets. But in robotic manipulation, data is both limited and expensive …

How can we imbue robots with the ability to manipulate objects precisely but also to reason
about them in terms of abstract concepts? Recent works in manipulation have shown that …

In neural networks, it is often desirable to work with various representations of the same
space. For example, 3D rotations can be represented with quaternions or Euler angles. In …

A key technical challenge in performing 6D object pose estimation from RGB-D image is to
fully leverage the two complementary data sources. Prior works either extract information …

This paper addresses the challenge of 6DoF pose estimation from a single RGB image
under severe occlusion or truncation. Many recent works have shown that a two-stage …

We introduce an approach for recovering the 6D pose of multiple known objects in a scene
captured by a set of input images with unknown camera viewpoints. First, we present a …

PointNet has revolutionized how we think about representing point clouds. For classification
and segmentation tasks, the approach and its subsequent variants/extensions are …

We present a near real-time (10Hz) method for 6-DoF tracking of an unknown object from a
monocular RGBD video sequence, while simultaneously performing neural 3D …