Pedestrian detection and tracking have become an important field in the computer vision
research area. This growing interest, started in the last decades, might be explained by the …

In the last few decades, Structure from Motion (SfM) and visual Simultaneous Localization
and Mapping (visual SLAM) techniques have gained significant interest from both the …

Humans are able to form a complex mental model of the environment they move in. This
mental model captures geometric and semantic aspects of the scene, describes the …

The assumption of scene rigidity is common in visual SLAM algorithms. However, it limits
their applicability in populated real-world environments. Furthermore, most scenarios …

Simultaneous localization and mapping (SLAM) consists in the concurrent construction of a
model of the environment (the map), and the estimation of the state of the robot moving …

Visual place recognition is a challenging problem due to the vast range of ways in which the
appearance of real-world places can vary. In recent years, improvements in visual sensing …

We present MaskFusion, a real-time, object-aware, semantic and dynamic RGB-D SLAM
system that goes beyond traditional systems which output a purely geometric map of a static …

We present a unified representation for actionable spatial perception: 3D Dynamic Scene
Graphs. Scene graphs are directed graphs where nodes represent entities in the scene (eg …

The Simultaneous Localization and Mapping (SLAM) technique has achieved astonishing
progress over the last few decades and has generated considerable interest in the …

Visual SLAM (simultaneous localization and mapping) refers to the problem of using
images, as the only source of external information, in order to establish the position of a …