activity
20182021
most citedVolumetric Instance-Aware Semantic Mapping and 3D Object Discovery

232 citations · 246 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2021

TSDF++: A Multi-Object Formulation for Dynamic Object Tracking and Reconstruction

Margarita Grinvald, Federico Tombari, Roland Siegwart +1

The ability to simultaneously track and reconstruct multiple objects moving in the scene is of the utmost importance for robotic tasks such as autonomous navigation and interaction…

cs.CV2020★ 2 cited

3DSNet: Unsupervised Shape-to-Shape 3D Style Transfer

Mattia Segu, Margarita Grinvald, Roland Siegwart +1

Transferring the style from one image onto another is a popular and widely studied task in computer vision. Yet, style transfer in the 3D setting remains a largely unexplored probl…

cs.RO2020★ 12 cited

Go Fetch: Mobile Manipulation in Unstructured Environments

Kenneth Blomqvist, Michel Breyer, Andrei Cramariuc +7

With humankind facing new and increasingly large-scale challenges in the medical and domestic spheres, automation of the service sector carries a tremendous potential for improved…

cs.RO2019★ 232 cited

Volumetric Instance-Aware Semantic Mapping and 3D Object Discovery

Margarita Grinvald, Fadri Furrer, Tonci Novkovic +4

To autonomously navigate and plan interactions in real-world environments, robots require the ability to robustly perceive and map complex, unstructured surrounding scenes. Besides…

cs.RO2018

Incremental Object Database: Building 3D Models from Multiple Partial Observations

Fadri Furrer, Tonci Novkovic, Marius Fehr +5

Collecting 3D object datasets involves a large amount of manual work and is time consuming. Getting complete models of objects either requires a 3D scanner that covers all the surf…