119 citations · 161 across the 8 of their papers we have counts for
8 papers
Multimodal Metadata Assignment for Cultural Heritage Artifacts
Luis Rei, Dunja Mladenić, Mareike Dorozynski +5
We develop a multimodal classifier for the cultural heritage domain using a late fusion approach and introduce a novel dataset. The three modalities are Image, Text, and Tabular da…
Depth-aware Panoptic Segmentation
Tuan Nguyen, Max Mehltretter, Franz Rottensteiner
Panoptic segmentation unifies semantic and instance segmentation and thus delivers a semantic class label and, for so-called thing classes, also an instance label per pixel. The di…
Appearance Based Deep Domain Adaptation for the Classification of Aerial Images
Dennis Wittich, Franz Rottensteiner
This paper addresses domain adaptation for the pixel-wise classification of remotely sensed data using deep neural networks (DNN) as a strategy to reduce the requirements of DNN wi…
Pose Estimation and 3D Reconstruction of Vehicles from Stereo-Images Using a Subcategory-Aware Shape Prior
Max Coenen, Franz Rottensteiner
The 3D reconstruction of objects is a prerequisite for many highly relevant applications of computer vision such as mobile robotics or autonomous driving. To deal with the inverse…
A hierarchical deep learning framework for the consistent classification of land use objects in geospatial databases
Chun Yang, Franz Rottensteiner, Christian Heipke
Land use as contained in geospatial databases constitutes an essential input for different applica-tions such as urban management, regional planning and environmental monitoring. I…
The Hessigheim 3D (H3D) Benchmark on Semantic Segmentation of High-Resolution 3D Point Clouds and Textured Meshes from UAV LiDAR and Multi-View-Stereo
Michael Kölle, Dominik Laupheimer, Stefan Schmohl +4
Automated semantic segmentation and object detection are of great importance in geospatial data analysis. However, supervised machine learning systems such as convolutional neural…
Probabilistic Vehicle Reconstruction Using a Multi-Task CNN
Max Coenen, Franz Rottensteiner
The retrieval of the 3D pose and shape of objects from images is an ill-posed problem. A common way to object reconstruction is to match entities such as keypoints, edges, or conto…
A two-layer Conditional Random Field for the classification of partially occluded objects
Sergey Kosov, Pushmeet Kohli, Franz Rottensteiner +1
Conditional Random Fields (CRF) are among the most popular techniques for image labelling because of their flexibility in modelling dependencies between the labels and the image fe…