35 citations · 92 across the 11 of their papers we have counts for
15 papers
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…
Field Robot for High-throughput and High-resolution 3D Plant Phenotyping
Felix Esser, Radu Alexandru Rosu, André Cornelißen +3
With the need to feed a growing world population, the efficiency of crop production is of paramount importance. To support breeding and field management, various characteristics of…
PermutoSDF: Fast Multi-View Reconstruction with Implicit Surfaces using Permutohedral Lattices
Radu Alexandru Rosu, Sven Behnke
Neural radiance-density field methods have become increasingly popular for the task of novel-view rendering. Their recent extension to hash-based positional encoding ensures fast t…
Neural Strands: Learning Hair Geometry and Appearance from Multi-View Images
Radu Alexandru Rosu, Shunsuke Saito, Ziyan Wang +3
We present Neural Strands, a novel learning framework for modeling accurate hair geometry and appearance from multi-view image inputs. The learned hair model can be rendered in rea…
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…
Target Chase, Wall Building, and Fire Fighting: Autonomous UAVs of Team NimbRo at MBZIRC 2020
Marius Beul, Max Schwarz, Jan Quenzel +11
The Mohamed Bin Zayed International Robotics Challenge (MBZIRC) 2020 posed diverse challenges for unmanned aerial vehicles (UAVs). We present our four tailored UAVs, specifically d…
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…
NeuralMVS: Bridging Multi-View Stereo and Novel View Synthesis
Radu Alexandru Rosu, Sven Behnke
Multi-View Stereo (MVS) is a core task in 3D computer vision. With the surge of novel deep learning methods, learned MVS has surpassed the accuracy of classical approaches, but sti…
EasyPBR: A Lightweight Physically-Based Renderer
Radu Alexandru Rosu, Sven Behnke
Modern rendering libraries provide unprecedented realism, producing real-time photorealistic 3D graphics on commodity hardware. Visual fidelity, however, comes at the cost of incre…
Visually Guided Balloon Popping with an Autonomous MAV at MBZIRC 2020
Marius Beul, Simon Bultmann, Andre Rochow +4
Visually guided control of micro aerial vehicles (MAV) demands for robust real-time perception, fast trajectory generation, and a capable flight platform. We present a fully autono…
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…
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.…
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…
Semi-Supervised Semantic Mapping through Label Propagation with Semantic Texture Meshes
Radu Alexandru Rosu, Jan Quenzel, Sven Behnke
Scene understanding is an important capability for robots acting in unstructured environments. While most SLAM approaches provide a geometrical representation of the scene, a seman…
Team NimbRo at MBZIRC 2017: Fast Landing on a Moving Target and Treasure Hunting with a Team of MAVs
Marius Beul, Matthias Nieuwenhuisen, Jan Quenzel +5
The Mohamed Bin Zayed International Robotics Challenge (MBZIRC) 2017 has defined ambitious new benchmarks to advance the state-of-the-art in autonomous operation of ground-based an…