8 citations · 20 across the 6 of their papers we have counts for
6 papers
GRAP-MOT: Unsupervised Graph-based Position Weighted Person Multi-camera Multi-object Tracking in a Highly Congested Space
Marek Socha, Michał Marczyk, Aleksander Kempski +4
GRAP-MOT is a new approach for solving the person MOT problem dedicated to videos of closed areas with overlapping multi-camera views, where person occlusion frequently occurs. Our…
Development of a Realistic Crowd Simulation Environment for Fine-grained Validation of People Tracking Methods
Paweł Foszner, Agnieszka Szczęsna, Luca Ciampi +7
Generally, crowd datasets can be collected or generated from real or synthetic sources. Real data is generated by using infrastructure-based sensors (such as static cameras or othe…
CrowdSim2: an Open Synthetic Benchmark for Object Detectors
Paweł Foszner, Agnieszka Szczęsna, Luca Ciampi +7
Data scarcity has become one of the main obstacles to developing supervised models based on Artificial Intelligence in Computer Vision. Indeed, Deep Learning-based models systemati…
POLCOVID: a multicenter multiclass chest X-ray database (Poland, 2020-2021)
Aleksandra Suwalska, Joanna Tobiasz, Wojciech Prazuch +20
The outbreak of the SARS-CoV-2 pandemic has put healthcare systems worldwide to their limits, resulting in increased waiting time for diagnosis and required medical assistance. Wit…
CIRCA: comprehensible online system in support of chest X-rays-based COVID-19 diagnosis
Wojciech Prazuch, Aleksandra Suwalska, Marek Socha +19
Due to the large accumulation of patients requiring hospitalization, the COVID-19 pandemic disease caused a high overload of health systems, even in developed countries. Deep learn…
Classification supporting COVID-19 diagnostics based on patient survey data
Joanna Henzel, Joanna Tobiasz, Michał Kozielski +11
Distinguishing COVID-19 from other flu-like illnesses can be difficult due to ambiguous symptoms and still an initial experience of doctors. Whereas, it is crucial to filter out th…