activity
20192025
most citedTeam NimbRo at MBZIRC 2017: Fast Landing on a Moving Target and Treasure Hunting with a Team of MAVs

35 citations · 86 across the 8 of their papers we have counts for

collaborators
Showing cs.CVShow all

7 papers · 1 filter

cs.CV2025

DiffLocks: Generating 3D Hair from a Single Image using Diffusion Models

Radu Alexandru Rosu, Keyu Wu, Yao Feng +2

We address the task of generating 3D hair geometry from a single image, which is challenging due to the diversity of hairstyles and the lack of paired image-to-3D hair data. Previo…

cs.CV2022★ 1 cited

Abstract Flow for Temporal Semantic Segmentation on the Permutohedral Lattice

Peer Schütt, Radu Alexandru Rosu, Sven Behnke

Semantic segmentation is a core ability required by autonomous agents, as being able to distinguish which parts of the scene belong to which object class is crucial for navigation…

cs.CV2021

LatticeNet: Fast Spatio-Temporal Point Cloud Segmentation Using Permutohedral Lattices

Radu Alexandru Rosu, Peer Schütt, Jan Quenzel +1

Deep convolutional neural networks (CNNs) have shown outstanding performance in the task of semantically segmenting images. Applying the same methods on 3D data still poses challen…

cs.CV2020

Beyond Photometric Consistency: Gradient-based Dissimilarity for Improving Visual Odometry and Stereo Matching

Jan Quenzel, Radu Alexandru Rosu, Thomas Läbe +2

Pose estimation and map building are central ingredients of autonomous robots and typically rely on the registration of sensor data. In this paper, we investigate a new metric for…

cs.CV2019★ 3 cited

Bonn Activity Maps: Dataset Description

Julian Tanke, Oh-Hun Kwon, Patrick Stotko +9

The key prerequisite for accessing the huge potential of current machine learning techniques is the availability of large databases that capture the complex relations of interest.…

cs.CV2019

LatticeNet: Fast Point Cloud Segmentation Using Permutohedral Lattices

Radu Alexandru Rosu, Peer Schütt, Jan Quenzel +1

Deep convolutional neural networks (CNNs) have shown outstanding performance in the task of semantically segmenting images. However, applying the same methods on 3D data still pose…