6 citations · 6 across the 8 of their papers we have counts for
3 papers · 1 filter
Regularizing Self-supervised 3D Scene Flows with Surface Awareness and Cyclic Consistency
Patrik Vacek, David Hurych, Karel Zimmermann +2
Learning without supervision how to predict 3D scene flows from point clouds is essential to many perception systems. We propose a novel learning framework for this task which impr…
T-UDA: Temporal Unsupervised Domain Adaptation in Sequential Point Clouds
Awet Haileslassie Gebrehiwot, David Hurych, Karel Zimmermann +2
Deep perception models have to reliably cope with an open-world setting of domain shifts induced by different geographic regions, sensor properties, mounting positions, and several…
MonoForce: Self-supervised Learning of Physics-informed Model for Predicting Robot-terrain Interaction
Ruslan Agishev, Karel Zimmermann, Vladimír Kubelka +2
While autonomous navigation of mobile robots on rigid terrain is a well-explored problem, navigating on deformable terrain such as tall grass or bushes remains a challenge. To addr…