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

In this paper, we present a comprehensive review of the imbalance problems in object
detection. To analyze the problems in a systematic manner, we introduce a problem-based …

Abstract 6D pose estimation from a single RGB image is a fundamental task in computer
vision. The current top-performing deep learning-based methods rely on an indirect strategy …

We present iNeRF, a framework that performs mesh-free pose estimation by" inverting" a
Neural Radiance Field (NeRF). NeRFs have been shown to be remarkably effective for the …

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 …

In this work, we present FFB6D, a full flow bidirectional fusion network designed for 6D pose
estimation from a single RGBD image. Our key insight is that appearance information in the …

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 present the evaluation methodology, datasets and results of the BOP Challenge 2022,
the fourth in a series of public competitions organized with the goal to capture the status quo …

This paper presents the evaluation methodology, datasets, and results of the BOP
Challenge 2020, the third in a series of public competitions organized with the goal to …