Related papers: LRDDv3: High-Resolution Long-Range Drone Detection…
The emergence of tethered drones represents a major advancement in unmanned aerial vehicles (UAVs) offering solutions to key limitations faced by traditional drones. This article explores the potential of tethered drones with a particular…
This paper presents an advanced mapping system that combines drone imagery with machine learning and computer vision to overcome challenges in speed, accuracy, and adaptability across diverse terrains. By automating processes like feature…
Sensor fusion is crucial for an accurate and robust perception system on autonomous vehicles. Most existing datasets and perception solutions focus on fusing cameras and LiDAR. However, the collaboration between camera and radar is…
Unmanned Aerial Vehicles (UAVs), have intrigued different people from all walks of life, because of their pervasive computing capabilities. UAV equipped with vision techniques, could be leveraged to establish navigation autonomous control…
Object detection from images captured by Unmanned Aerial Vehicles (UAVs) is becoming increasingly useful. Despite the great success of the generic object detection methods trained on ground-to-ground images, a huge performance drop is…
The rapid rise of accessibility of unmanned aerial vehicles or drones pose a threat to general security and confidentiality. Most of the commercially available or custom-built drones are multi-rotors and are comprised of multiple…
Considering the accelerated development of Unmanned Aerial Vehicles (UAVs) applications in both industrial and research scenarios, there is an increasing need for localizing these aerial systems in non-urban environments, using GNSS-Free,…
We aim to detect and identify multiple objects using multiple cameras and computer vision for disaster response drones. The major challenges are taming detection errors, resolving ID switching and fragmentation, adapting to multi-scale…
Intrinsic image decomposition (IID) of outdoor scenes is crucial for relighting, editing, and understanding large-scale environments, but progress has been limited by the lack of real-world datasets with reliable albedo and shading…
3D object detection at long range is crucial for ensuring the safety and efficiency of self driving vehicles, allowing them to accurately perceive and react to objects, obstacles, and potential hazards from a distance. But most current…
Drones have become essential tools in a wide range of industries, including agriculture, surveying, and transportation. However, tracking unmanned aerial vehicles (UAVs) in challenging environments, such cluttered or GNSS-denied…
A drone monitoring system that integrates deep-learning-based detection and tracking modules is proposed in this work. The biggest challenge in adopting deep learning methods for drone detection is the limited amount of training drone…
Climate change is leading to more and more extreme weather events such as heavy rainfall and flooding. This technical report deals with the question of how rescue commanders can be better and faster provided with current information during…
Unmanned aerial vehicles, commonly known as drones, have emerged as a disruptive technology with the potential to revolutionize operations across various industries. Drones are the fast-growing internet-of-things technology and are…
Cross-view image matching aims to match images of the same target scene acquired from different platforms. With the rapid development of drone technology, cross-view matching by neural network models has been a widely accepted choice for…
This paper presents a Light Detection and Ranging (LiDAR) data set that targets complex urban environments. Urban environments with high-rise buildings and congested traffic pose a significant challenge for many robotics applications. The…
Purpose: This paper presents a new dataset of Aerial Imagery from Robotics simulator (abbr. AIR). AIR dataset aims to provide a starting point for localization system development and to become a typical benchmark for accuracy comparison of…
Assessing collision risk is a critical challenge to effective traffic safety management. The deployment of unmanned aerial vehicles (UAVs) to address this issue has shown much promise, given their wide visual field and movement flexibility.…
In recent years, the increasing prevalence and intensity of wildfires have posed significant challenges to emergency response teams. The utilization of unmanned aerial vehicles (UAVs), commonly known as drones, has shown promise in aiding…
Drones equipped with cameras can significantly enhance human ability to perceive the world because of their remarkable maneuverability in 3D space. Ironically, object detection for drones has always been conducted in the 2D image space,…