22 citations · 38 across the 6 of their papers we have counts for
6 papers
Drones4Good: Supporting Disaster Relief Through Remote Sensing and AI
Nina Merkle, Reza Bahmanyar, Corentin Henry +8
In order to respond effectively in the aftermath of a disaster, emergency services and relief organizations rely on timely and accurate information about the affected areas. Remote…
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…
EAGLE: Large-scale Vehicle Detection Dataset in Real-World Scenarios using Aerial Imagery
Seyed Majid Azimi, Reza Bahmanyar, Corenin Henry +1
Multi-class vehicle detection from airborne imagery with orientation estimation is an important task in the near and remote vision domains with applications in traffic monitoring a…
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…
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…