UAV (Unmanned Aerial Vehicles): Diverse Applications of UAV Datasets in Segmentation, Classification, Detection, and Tracking

TL;DR

This paper reviews the diverse applications of UAV datasets in computer vision tasks such as segmentation, classification, detection, and tracking, highlighting their importance in advancing research and practical solutions across various domains.

Contribution

It provides a comprehensive overview of UAV datasets, categorizing their types and illustrating their pivotal role in enabling advanced models for multiple aerial applications.

Findings

UAV datasets include unimodal and multimodal data types.

They are crucial for tasks like disaster assessment and aerial surveillance.

UAV datasets enhance model capabilities in complex environments.

Abstract

Unmanned Aerial Vehicles (UAVs), have greatly revolutionized the process of gathering and analyzing data in diverse research domains, providing unmatched adaptability and effectiveness. This paper presents a thorough examination of Unmanned Aerial Vehicle (UAV) datasets, emphasizing their wide range of applications and progress. UAV datasets consist of various types of data, such as satellite imagery, images captured by drones, and videos. These datasets can be categorized as either unimodal or multimodal, offering a wide range of detailed and comprehensive information. These datasets play a crucial role in disaster damage assessment, aerial surveillance, object recognition, and tracking. They facilitate the development of sophisticated models for tasks like semantic segmentation, pose estimation, vehicle re-identification, and gesture recognition. By leveraging UAV datasets, researchers can significantly enhance the capabilities of computer vision models, thereby advancing technology and improving our understanding of complex, dynamic environments from an aerial perspective. This review aims to encapsulate the multifaceted utility of UAV datasets, emphasizing their pivotal role in driving innovation and practical applications in multiple domains.