Nowadays, computer vision with 3D (dimension) object detection and 6D (degree of
freedom) pose assumptions are widely discussed and studied in the field. In the 3D object …

Object pose recovery has gained increasing attention in the computer vision field as it has
become an important problem in rapidly evolving technological areas related to autonomous …

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 …

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 …

In this work, we present a novel data-driven method for robust 6DoF object pose estimation
from a single RGBD image. Unlike previous methods that directly regressing pose …

In this paper we present a novel deep learning method for 3D object detection and 6D pose
estimation from RGB images. Our method, named DPOD (Dense Pose Object Detector) …

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 …

Estimating the 6D pose of objects from images is an important problem in various
applications such as robot manipulation and virtual reality. While direct regression of images …

We propose a single-shot approach for simultaneously detecting an object in an RGB image
and predicting its 6D pose without requiring multiple stages or having to examine multiple …