3 citations · 5 across the 6 of their papers we have counts for
7 papers
Multi-Object Navigation in real environments using hybrid policies
Assem Sadek, Guillaume Bono, Boris Chidlovskii +2
Navigation has been classically solved in robotics through the combination of SLAM and planning. More recently, beyond waypoint planning, problems involving significant components…
Learning whom to trust in navigation: dynamically switching between classical and neural planning
Sombit Dey, Assem Sadek, Gianluca Monaci +2
Navigation of terrestrial robots is typically addressed either with localization and mapping (SLAM) followed by classical planning on the dynamically created maps, or by machine le…
Learning with a Mole: Transferable latent spatial representations for navigation without reconstruction
Guillaume Bono, Leonid Antsfeld, Assem Sadek +2
Agents navigating in 3D environments require some form of memory, which should hold a compact and actionable representation of the history of observations useful for decision takin…
An in-depth experimental study of sensor usage and visual reasoning of robots navigating in real environments
Assem Sadek, Guillaume Bono, Boris Chidlovskii +1
Visual navigation by mobile robots is classically tackled through SLAM plus optimal planning, and more recently through end-to-end training of policies implemented as deep networks…
Universal Domain Adaptation in Ordinal Regression
Boris Chidlovskii, Assem Sadek, Christian Wolf
We address the problem of universal domain adaptation (UDA) in ordinal regression (OR), which attempts to solve classification problems in which labels are not independent, but fol…
Adversarial Transfer of Pose Estimation Regression
Boris Chidlovskii, Assem Sadek
We address the problem of camera pose estimation in visual localization. Current regression-based methods for pose estimation are trained and evaluated scene-wise. They depend on t…
Self-Supervised Attention Learning for Depth and Ego-motion Estimation
Assem Sadek, Boris Chidlovskii
We address the problem of depth and ego-motion estimation from image sequences. Recent advances in the domain propose to train a deep learning model for both tasks using image reco…