activity
20182020
most citedMRCNet: Crowd Counting and Density Map Estimation in Aerial and Ground Imagery

22 citations · 22 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2020

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…

cs.CV2020

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…

cs.CV2020

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…

cs.CV201922 cited

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…

cs.CV2018

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…