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20162020
most citedMRCNet: Crowd Counting and Density Map Estimation in Aerial and Ground Imagery

22 citations · 23 across the 2 of their papers we have counts for

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5 papers · 1 filter

cs.CV20201 cited

SkyScapes -- Fine-Grained Semantic Understanding of Aerial Scenes

Seyed Majid Azimi, Corentin Henry, Lars Sommer +2

Understanding the complex urban infrastructure with centimeter-level accuracy is essential for many applications from autonomous driving to mapping, infrastructure monitoring, and…

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…

cs.CV2018

End-to-End Saliency Mapping via Probability Distribution Prediction

Saumya Jetley, Naila Murray, Eleonora Vig

Most saliency estimation methods aim to explicitly model low-level conspicuity cues such as edges or blobs and may additionally incorporate top-down cues using face or text detecti…

cs.CV2016

Virtual Worlds as Proxy for Multi-Object Tracking Analysis

Adrien Gaidon, Qiao Wang, Yohann Cabon +1

Modern computer vision algorithms typically require expensive data acquisition and accurate manual labeling. In this work, we instead leverage the recent progress in computer graph…