A review of synthetic image data and its use in computer vision
Development of computer vision algorithms using convolutional neural networks and deep
learning has necessitated ever greater amounts of annotated and labelled data to produce …
learning has necessitated ever greater amounts of annotated and labelled data to produce …
Drone detection and defense systems: Survey and a software-defined radio-based solution
With the decrease in the cost and size of drones in recent years, their number has also
increased exponentially. As such, the concerns regarding security aspects that are raised by …
increased exponentially. As such, the concerns regarding security aspects that are raised by …
Detecting everything in the open world: Towards universal object detection
In this paper, we formally address universal object detection, which aims to detect every
scene and predict every category. The dependence on human annotations, the limited …
scene and predict every category. The dependence on human annotations, the limited …
Embracing single stride 3d object detector with sparse transformer
In LiDAR-based 3D object detection for autonomous driving, the ratio of the object size to
input scene size is significantly smaller compared to 2D detection cases. Overlooking this …
input scene size is significantly smaller compared to 2D detection cases. Overlooking this …
RFLA: Gaussian receptive field based label assignment for tiny object detection
Detecting tiny objects is one of the main obstacles hindering the development of object
detection. The performance of generic object detectors tends to drastically deteriorate on tiny …
detection. The performance of generic object detectors tends to drastically deteriorate on tiny …
RSOD: Real-time small object detection algorithm in UAV-based traffic monitoring
The prevailing applications of Unmanned Aerial Vehicles (UAVs) in transportation systems
promote the development of object detection methods to collect real-time traffic information …
promote the development of object detection methods to collect real-time traffic information …
QueryDet: Cascaded sparse query for accelerating high-resolution small object detection
While general object detection with deep learning has achieved great success in the past
few years, the performance and efficiency of detecting small objects are far from satisfactory …
few years, the performance and efficiency of detecting small objects are far from satisfactory …
VisDrone-DET2021: The vision meets drone object detection challenge results
Object detection on the drone faces a great diversity of challenges such as small object
inference, background clutter and wide viewpoint. In contrast to traditional detection problem …
inference, background clutter and wide viewpoint. In contrast to traditional detection problem …
Detecting tiny objects in aerial images: A normalized Wasserstein distance and a new benchmark
Tiny object detection (TOD) in aerial images is challenging since a tiny object only contains
a few pixels. State-of-the-art object detectors do not provide satisfactory results on tiny …
a few pixels. State-of-the-art object detectors do not provide satisfactory results on tiny …
Detection and tracking meet drones challenge
Drones, or general UAVs, equipped with cameras have been fast deployed with a wide
range of applications, including agriculture, aerial photography, and surveillance …
range of applications, including agriculture, aerial photography, and surveillance …