111 citations · 162 across the 7 of their papers we have counts for
8 papers
Multiple Pedestrians and Vehicles Tracking in Aerial Imagery: A Comprehensive Study
Seyed Majid Azimi, Maximilian Kraus, Reza Bahmanyar +1
In this paper, we address various challenges in multi-pedestrian and vehicle tracking in high-resolution aerial imagery by intensive evaluation of a number of traditional and Deep…
AerialMPTNet: Multi-Pedestrian Tracking in Aerial Imagery Using Temporal and Graphical Features
Maximilian Kraus, Seyed Majid Azimi, Emec Ercelik +3
Multi-pedestrian tracking in aerial imagery has several applications such as large-scale event monitoring, disaster management, search-and-rescue missions, and as input into predic…
MRCNet: Crowd Counting and Density Map Estimation in Aerial and Ground Imagery
Reza Bahmanyar, Elenora Vig, Peter Reinartz
In spite of the many advantages of aerial imagery for crowd monitoring and management at mass events, datasets of aerial images of crowds are still lacking in the field. As a remed…
Late or Earlier Information Fusion from Depth and Spectral Data? Large-Scale Digital Surface Model Refinement by Hybrid-cGAN
Ksenia Bittner, Marco Körner, Peter Reinartz
We present the workflow of a DSM refinement methodology using a Hybrid-cGAN where the generative part consists of two encoders and a common decoder which blends the spectral and he…
DSM Building Shape Refinement from Combined Remote Sensing Images based on Wnet-cGANs
Ksenia Bittner, Marco Körner, Peter Reinartz
We describe the workflow of a digital surface models (DSMs) refinement algorithm using a hybrid conditional generative adversarial network (cGAN) where the generative part consists…
Towards Multi-class Object Detection in Unconstrained Remote Sensing Imagery
Seyed Majid Azimi, Eleonora Vig, Reza Bahmanyar +2
Automatic multi-class object detection in remote sensing images in unconstrained scenarios is of high interest for several applications including traffic monitoring and disaster ma…
Aerial LaneNet: Lane Marking Semantic Segmentation in Aerial Imagery using Wavelet-Enhanced Cost-sensitive Symmetric Fully Convolutional Neural Networks
Seyed Majid Azimi, Peter Fischer, Marco Körner +1
The knowledge about the placement and appearance of lane markings is a prerequisite for the creation of maps with high precision, necessary for autonomous driving, infrastructure m…
Authorship Analysis based on Data Compression
Daniele Cerra, Mihai Datcu, Peter Reinartz
This paper proposes to perform authorship analysis using the Fast Compression Distance (FCD), a similarity measure based on compression with dictionaries directly extracted from th…