3 citations · 3 across the 1 of their papers we have counts for
6 papers
DynaSLAM II: Tightly-Coupled Multi-Object Tracking and SLAM
Berta Bescos, Carlos Campos, Juan D. Tardós +1
The assumption of scene rigidity is common in visual SLAM algorithms. However, it limits their applicability in populated real-world environments. Furthermore, most scenarios inclu…
Empty Cities: a Dynamic-Object-Invariant Space for Visual SLAM
Berta Bescos, Cesar Cadena, Jose Neira
In this paper we present a data-driven approach to obtain the static image of a scene, eliminating dynamic objects that might have been present at the time of traversing the scene…
Empty Cities: Image Inpainting for a Dynamic-Object-Invariant Space
Berta Bescos, José Neira, Roland Siegwart +1
In this paper we present an end-to-end deep learning framework to turn images that show dynamic content, such as vehicles or pedestrians, into realistic static frames. This objecti…
Dynamic Objects Segmentation for Visual Localization in Urban Environments
Guoxiang Zhou, Berta Bescos, Marcin Dymczyk +3
Visual localization and mapping is a crucial capability to address many challenges in mobile robotics. It constitutes a robust, accurate and cost-effective approach for local and g…
DynaSLAM: Tracking, Mapping and Inpainting in Dynamic Scenes
Berta Bescos, José M. Fácil, Javier Civera +1
The assumption of scene rigidity is typical in SLAM algorithms. Such a strong assumption limits the use of most visual SLAM systems in populated real-world environments, which are…
Sparse Optimization for Robust and Efficient Loop Closing
Yasir Latif, Guoquan Huang, John Leonard +1
It is essential for a robot to be able to detect revisits or loop closures for long-term visual navigation.A key insight explored in this work is that the loop-closing event inhere…