NBF_StreetView

This dataset is designed to simulate real-world challenges faced by autonomous vehicles, particularly when encountering degraded images through sensors in various street environments. It includes a diverse set of images from streetview and pedestrian walkways, subjected to various types of degradation such as noise, blur, and flare, mimicking the environmental conditions that can affect sensor performance in automotive applications. The dataset captures a variety of scenes, including vehicles, people, and street scenes, providing a comprehensive representation of potential challenges in visual processing. Ideal for deep learning and computer vision tasks, this dataset offers a robust resource for training and evaluating models focused on enhancing the resilience and accuracy of autonomous vehicle systems in degraded visual environments. Tasks such as image restoration, denoising, deblurring, and flare correction are well-suited to this dataset, making it an essential tool for advancing computer vision solutions within the automotive and urban infrastructure sectors.For more specific details on how this dataset was created, please feel free to reach out via email. Github: https://github.com/IsmailQayyum/NBF_StreetViewLicense:This work is licensed under CC By 4.0