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eCARLA-scenes: A synthetically generated dataset for event-based optical flow prediction - MaRDI portal

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eCARLA-scenes: A synthetically generated dataset for event-based optical flow prediction

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ECARLA-scenes: A synthetically generated dataset for event-based optical flow prediction



DOI10.5281/zenodo.14412251Zenodo14412251MaRDI QIDQ6696427

Dataset published at Zenodo repository.

Author name not available (Why is that?)

Publication date: 12 December 2024

Copyright license: No records found.



Description

This repository hosts a synthetic event-based optical flow dataset, meticulously designed to simulate diverse environments under varying weather conditions using the CARLA simulator. The dataset is specifically tailored for autonomous field vehicles, featuring event streams, grayscale images, and corresponding ground truth optical flow. In addition to the dataset, the accompanying repository provides a user-friendly pipeline for generating custom datasets, including optical flow displacements and grayscale images. The generated data leverages the optimized eWiz framework, ensuring efficient storage, access, and processing. The data generation pipeline can be utilized by cloning the eCARLA-scenes repository. Whether you're a researcher or developer, this resource is an ideal starting point for advancing event-based vision systems in real-world autonomous applications.






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