CARLA-BSP: a simulated dataset with pedestrians
Maciej Wielgosz, Antonio M. L\'opez, Muhammad Naveed Riaz
TL;DR
This paper introduces CARLA-BSP, a new simulated dataset with pedestrians generated via the ARCANE framework in CARLA, supporting various tasks like detection and pose estimation with baseline results.
Contribution
It presents a novel dataset generated with the ARCANE framework in CARLA, enabling diverse pedestrian-related computer vision tasks.
Findings
Baseline results for pedestrian detection and pose estimation.
Demonstration of dataset utility across multiple tasks.
Validation of ARCANE framework for dataset generation.
Abstract
We present a sample dataset featuring pedestrians generated using the ARCANE framework, a new framework for generating datasets in CARLA (0.9.13). We provide use cases for pedestrian detection, autoencoding, pose estimation, and pose lifting. We also showcase baseline results. For more information, visit https://project-arcane.eu/.
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Taxonomy
TopicsVideo Surveillance and Tracking Methods · Advanced Neural Network Applications · Human Pose and Action Recognition
MethodsEntropy Regularization · Proximal Policy Optimization · CARLA: An Open Urban Driving Simulator