no code implementations • 12 Apr 2024 • Patrik Vacek, David Hurych, Tomáš Svoboda, Karel Zimmermann
We identified the structural constraints and the use of large and strict rigid clusters as the main pitfall of the current approaches and we propose a novel clustering approach that allows for combination of overlapping soft clusters as well as non-overlapping rigid clusters representation.
1 code implementation • 12 Dec 2023 • Patrik Vacek, David Hurych, Karel Zimmermann, Patrick Perez, Tomas Svoboda
Learning without supervision how to predict 3D scene flows from point clouds is essential to many perception systems.
1 code implementation • 15 Sep 2023 • Awet Haileslassie Gebrehiwot, David Hurych, Karel Zimmermann, Patrick Pérez, Tomáš Svoboda
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 other reasons.
no code implementations • 9 Nov 2022 • Karel Zimmermann
We present a conceptually simple and intuitive method to calculate and to measure the dissimilarities among 2D shapes.
1 code implementation • 13 Jul 2022 • Awet Haileslassie Gebrehiwot, Patrik Vacek, David Hurych, Karel Zimmermann, Patrick Perez, Tomáš Svoboda
We propose to leverage sequences of point clouds to boost the pseudolabeling technique in a teacher-student setup via training multiple teachers, each with access to different temporal information.
no code implementations • ICCV 2017 • Karel Zimmermann, Tomas Petricek, Vojtech Salansky, Tomas Svoboda
We propose an active 3D mapping method for depth sensors, which allow individual control of depth-measuring rays, such as the newly emerging solid-state lidars.
no code implementations • 8 Dec 2016 • Martin Pecka, Karel Zimmermann, Michal Reinštein, Tomáš Svoboda
Mobile robots with complex morphology are essential for traversing rough terrains in Urban Search & Rescue missions (USAR).