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20182022
most citedContinuous-Time vs. Discrete-Time Vision-based SLAM: A Comparative Study

1 citations · 1 across the 1 of their papers we have counts for

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5 papers

cs.RO20221 cited

Continuous-Time vs. Discrete-Time Vision-based SLAM: A Comparative Study

Giovanni Cioffi, Titus Cieslewski, Davide Scaramuzza

Robotic practitioners generally approach the vision-based SLAM problem through discrete-time formulations. This has the advantage of a consolidated theory and very good understandi…

cs.CV2020

Augmenting Visual Place Recognition with Structural Cues

Amadeus Oertel, Titus Cieslewski, Davide Scaramuzza

In this paper, we propose to augment image-based place recognition with structural cues. Specifically, these structural cues are obtained using structure-from-motion, such that no…

cs.RO2019

Exploration Without Global Consistency Using Local Volume Consolidation

Titus Cieslewski, Andreas Ziegler, Davide Scaramuzza

In exploration, the goal is to build a map of an unknown environment. Most state-of-the-art approaches use map representations that require drift-free state estimates to function p…

cs.CV2018

Matching Features without Descriptors: Implicitly Matched Interest Points

Titus Cieslewski, Michael Bloesch, Davide Scaramuzza

The extraction and matching of interest points is a prerequisite for many geometric computer vision problems. Traditionally, matching has been achieved by assigning descriptors to…

cs.CV2018

SIPs: Succinct Interest Points from Unsupervised Inlierness Probability Learning

Titus Cieslewski, Konstantinos G. Derpanis, Davide Scaramuzza

A wide range of computer vision algorithms rely on identifying sparse interest points in images and establishing correspondences between them. However, only a subset of the initial…