Multimodal image matching, which refers to identifying and then corresponding the same or
similar structure/content from two or more images that are of significant modalities or …

In this paper, we propose a survey of the Simultaneous Localization And Mapping (SLAM)
field when considering the recent evolution of autonomous driving. The growing interest …

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

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

Place recognition in 3D data is a challenging task that has been commonly approached by
adapting image-based solutions. Methods based on local features suffer from ambiguity and …

Autonomous systems will play an essential role in many applications across diverse
domains including space, marine, air, field, road, and service robotics. They will assist us in …

We are surrounded by plenty of information about our environment. From these multiple
sources, numerous data could be extracted: set of images, 3D model, coloured points …

Long‐term operation of robots creates new challenges to Simultaneous Localization and
Mapping (SLAM) algorithms. Long‐term SLAM algorithms should adapt to recent changes …

Robust cross-seasonal localization is one of the major challenges in long-term visual
navigation of autonomous vehicles. In this paper, we exploit recent advances in semantic …

Deep learning has become the standard model for object detection and recognition.
Recently, there is progress on using CNN models for geometric vision tasks like depth …