A state-of-the-art review on mobile robotics tasks using artificial intelligence and visual data
Nowadays, the field of mobile robotics has experienced an important evolution and these
robots are more commonly proposed to solve different tasks autonomously. The use of …
robots are more commonly proposed to solve different tasks autonomously. The use of …
[HTML][HTML] A survey on deep learning-based monocular spacecraft pose estimation: Current state, limitations and prospects
Estimating the pose of an uncooperative spacecraft is an important computer vision problem
for enabling the deployment of automatic vision-based systems in orbit, with applications …
for enabling the deployment of automatic vision-based systems in orbit, with applications …
The apolloscape dataset for autonomous driving
Scene parsing aims to assign a class (semantic) label for each pixel in an image. It is a
comprehensive analysis of an image. Given the rise of autonomous driving, pixel-accurate …
comprehensive analysis of an image. Given the rise of autonomous driving, pixel-accurate …
Understanding the limitations of cnn-based absolute camera pose regression
Visual localization is the task of accurate camera pose estimation in a known scene. It is a
key problem in computer vision and robotics, with applications including self-driving cars …
key problem in computer vision and robotics, with applications including self-driving cars …
Benchmarking 6dof outdoor visual localization in changing conditions
Visual localization enables autonomous vehicles to navigate in their surroundings and
augmented reality applications to link virtual to real worlds. Practical visual localization …
augmented reality applications to link virtual to real worlds. Practical visual localization …
Geometric loss functions for camera pose regression with deep learning
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 …
relocalisation. In particular, PoseNet is a deep convolutional neural network which learns to …
Undeepvo: Monocular visual odometry through unsupervised deep learning
We propose a novel monocular visual odometry (VO) system called UnDeepVO in this
paper. UnDeepVO is able to estimate the 6-DoF pose of a monocular camera and the depth …
paper. UnDeepVO is able to estimate the 6-DoF pose of a monocular camera and the depth …
Geometry-aware learning of maps for camera localization
Maps are a key component in image-based camera localization and visual SLAM systems:
they are used to establish geometric constraints between images, correct drift in relative …
they are used to establish geometric constraints between images, correct drift in relative …
Codeslam—learning a compact, optimisable representation for dense visual slam
The representation of geometry in real-time 3D perception systems continues to be a critical
research issue. Dense maps capture complete surface shape and can be augmented with …
research issue. Dense maps capture complete surface shape and can be augmented with …
Long-term visual localization revisited
Visual localization enables autonomous vehicles to navigate in their surroundings and
augmented reality applications to link virtual to real worlds. Practical visual localization …
augmented reality applications to link virtual to real worlds. Practical visual localization …