F1 racing cars tracking through transfer learning

In this project we make use of transfer learning (Pan and Yang, 2009), by fine-tuning a pre-trained faster R-CNN model with a ResNet-50-FPN backbone (Ren et al., 2015), to develop a pipeline for detection and tracking of F1 racing cars, enhanced with histograms distance.

For further information, you can read the presentation slides.

This project has been developed during the A.Y. 2021-2022 for the Computer Vision course @ Sapienza University of Rome.

Install all the python dependencies:

pip install -r requirements.txt

• Andrea Gasparini
• Edoardo Di Paolo