Seyed Majid Azimi — accepted AI-conference papers

2024

VETRA: A Dataset for Vehicle Tracking in Aerial Imagery - New Challenges for Multi-Object Tracking

Jens Hellekes*, Manuel Mühlhaus, Reza Bahmanyar, Seyed Majid Azimi, Franz Kurz

ECCV 2024oral

"The informative power of traffic analysis can be enhanced by considering changes in both time and space. Vehicle tracking algorithms applied to drone videos provide a better overview than street-level surveillance cameras. However, existing aerial MOT datasets only address stationary settings, leav…

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2019

SkyScapes Fine-Grained Semantic Understanding of Aerial Scenes

Seyed Majid Azimi, Corentin Henry, Lars Sommer, Arne Schumann, Eleonora Vig

ICCV 2019poster

Understanding the complex urban infrastructure with centimeter-level accuracy is essential for many applications from autonomous driving to mapping, infrastructure monitoring, and urban management. Aerial images provide valuable information over a large area instantaneously; nevertheless, no current…

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