This paper is an overview to Visual Simultaneous Localization and Mapping (V-SLAM). We
discuss the basic definitions in the SLAM and vision system fields and provide a review of …

The construction industry is one of the world's largest industries, with an annual budget of
$10 trillion globally. Despite its size, the efficiency and growth in labour productivity in the …

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 …

Camera pose estimation is a long-standing computer vision problem that to date often relies
on classical methods, such as handcrafted keypoint matching, RANSAC and bundle …

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 …

Establishing correspondences from image to 3D has been a key task of 6DoF object pose
estimation for a long time. To predict pose more accurately, deeply learned dense maps …

Camera pose estimation in known scenes is a 3D geometry task recently tackled by multiple
learning algorithms. Many regress precise geometric quantities, like poses or 3D points …

The last decade witnessed increasingly rapid progress in self‐driving vehicle technology,
mainly backed up by advances in the area of deep learning and artificial intelligence (AI) …

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 …

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