Autonomous driving vehicles require both a precise localization and mapping solution in
different driving environment. In this context, Simultaneous Localization and Mapping …

Grounding language to the visual observations of a navigating agent can be performed
using off-the-shelf visual-language models pretrained on Internet-scale data (eg, image …

We present a near real-time (10Hz) method for 6-DoF tracking of an unknown object from a
monocular RGBD video sequence, while simultaneously performing neural 3D …

We present vMAP, an object-level dense SLAM system using neural field representations.
Each object is represented by a small MLP, enabling efficient, watertight object modelling …

3D scene graphs have recently emerged as a powerful high-level representation of 3D
environments. A 3D scene graph describes the environment as a layered graph where …

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 …

We provide an open-source C++ library for real-time metric-semantic visual-inertial
Simultaneous Localization And Mapping (SLAM). The library goes beyond existing visual …

Multi-robot simultaneous localization and mapping (SLAM) is a crucial capability to obtain
timely situational awareness over large areas. Real-world applications demand multi-robot …

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

Static environment is a prerequisite for most of visual simultaneous localization and
mapping systems. Such a strong assumption limits the practical application of most existing …