Abstract Purpose of Review This review provides a comprehensive overview of machine
learning approaches for vision-based robotic gras** and manipulation. Current trends and …

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 …

As a fundamental and critical task in various visual applications, image matching can identify
then correspond the same or similar structure/content from two or more images. Over the …

Image-to-image translation aims to learn the map** between two visual domains. There
are two main challenges for many applications: 1) the lack of aligned training pairs and 2) …

Estimating the 6D pose of known objects is important for robots to interact with the real
world. The problem is challenging due to the variety of objects as well as the complexity of a …

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 …

For machine learning systems to be reliable, we must understand their performance in
unseen, out-of-distribution environments. In this paper, we empirically show that out-of …

The cost of large scale data collection and annotation often makes the application of
machine learning algorithms to new tasks or datasets prohibitively expensive. One approach …

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 …