Recent years have witnessed enormous progress in AI-related fields such as computer
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …

Camera localization involves the estimation of the camera pose of an image from a random
scene. We used a single image or sequence of images or videos as the input. The output …

We propose a new method for object pose estimation without CAD models. The previous
feature-matching-based method OnePose has shown promising results under a one-shot …

Deep learning has shown to be effective for robust and real-time monocular image
relocalisation. In particular, PoseNet is a deep convolutional neural network which learns to …

We describe a learning-based system that estimates the camera position and orientation
from a single input image relative to a known environment. The system is flexible wrt the …

Popular research areas like autonomous driving and augmented reality have renewed the
interest in image-based camera localization. In this work, we address the task of predicting …

Accurately determining the position and orientation from which an image was taken, ie,
computing the camera pose, is a fundamental step in many Computer Vision applications …

Visual localization enables autonomous vehicles to navigate in their surroundings and
augmented reality applications to link virtual to real worlds. Practical visual localization …

An established approach for 3D point cloud registration is to estimate the registration
function from 3D keypoint correspondences. Typically, a robust technique is required to …

Accurately estimating a robot's pose relative to a global scene model and precisely tracking
the pose in real-time is a fundamental problem for navigation and obstacle avoidance tasks …