论文标题
审查6D对象姿势估计，重点是室内场景的理解
Review on 6D Object Pose Estimation with the focus on Indoor Scene Understanding
论文作者
论文摘要
6D对象姿势估计问题已在计算机视觉和机器人技术领域进行了广泛的研究。它具有广泛的应用程序，例如机器人操纵，增强现实和3D场景的理解。随着深度学习的出现，已经取得了许多突破。但是，当他们遇到看不见的实例，新类别或现实世界中的挑战，例如混乱的背景和遮挡时，方法将继续挣扎。在这项研究中，我们将基于输入方式，问题表述以及它是类别级别还是实例级别的方法来探讨可用方法。作为讨论的一部分，我们将重点介绍6D对象姿势估计如何用于理解3D场景。
6D object pose estimation problem has been extensively studied in the field of Computer Vision and Robotics. It has wide range of applications such as robot manipulation, augmented reality, and 3D scene understanding. With the advent of Deep Learning, many breakthroughs have been made; however, approaches continue to struggle when they encounter unseen instances, new categories, or real-world challenges such as cluttered backgrounds and occlusions. In this study, we will explore the available methods based on input modality, problem formulation, and whether it is a category-level or instance-level approach. As a part of our discussion, we will focus on how 6D object pose estimation can be used for understanding 3D scenes.
