33 citations · 124 across the 13 of their papers we have counts for
7 papers · 1 filter
Let-It-Flow: Simultaneous Optimization of 3D Flow and Object Clustering
Patrik Vacek, David Hurych, Tomáš Svoboda +1
We study the problem of self-supervised 3D scene flow estimation from real large-scale raw point cloud sequences, which is crucial to various tasks like trajectory prediction or in…
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…
Real3D-Aug: Point Cloud Augmentation by Placing Real Objects with Occlusion Handling for 3D Detection and Segmentation
Petr Šebek, Šimon Pokorný, Patrik Vacek +1
Object detection and semantic segmentation with the 3D lidar point cloud data require expensive annotation. We propose a data augmentation method that takes advantage of already an…
Teachers in concordance for pseudo-labeling of 3D sequential data
Awet Haileslassie Gebrehiwot, Patrik Vacek, David Hurych +3
Automatic pseudo-labeling is a powerful tool to tap into large amounts of sequential unlabeled data. It is specially appealing in safety-critical applications of autonomous driving…
PreCNet: Next-Frame Video Prediction Based on Predictive Coding
Zdenek Straka, Tomas Svoboda, Matej Hoffmann
Predictive coding, currently a highly influential theory in neuroscience, has not been widely adopted in machine learning yet. In this work, we transform the seminal model of Rao a…
Learning for Active 3D Mapping
Karel Zimmermann, Tomas Petricek, Vojtech Salansky +1
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. The method simultan…