Enriching Diversity of Synthetic Images for Person Detection

Camera-based patient monitoring is undergoing rapid adoption in the healthcare sector with the recent COVID-19 pandemic acting as a catalyst. It offers round-the-clock monitoring of patients in clinical units (e.g. ICUs, ORs), or at their homes through installed cameras, enabling timely, pre-emptive care. These are powered by Computer Vision...

Pedestrian Detection and Tracking for Mobile Robots in Human Environments

With the performance of current motion planning methods being highly dependent on the quality of the perception system, robust 3D multi-object detection and tracking are vital for autonomous driving applications. Despite all the advancements in 2D and 3D object detectors, robust tracking of pedestrians in dense scenarios is still a challenging...

Binary Neural Networks for Object Detection

In the past few years, convolutional neural networks (CNNs) have been widely utilized and shown state-of-the-art performances on computer vision tasks. However, CNN based approaches usually require a large amount of storage, run-time memory, as well as computation power in both training and inference time, which are usually used on GPU based...

Detecting Empty Wireframe Objects on Micro-Air Vehicles: Applied for Gate Detection in Autonomous Drone Racing

Autonomous MAV are an emerging technology that supports a wide range of applications such as medical delivery or finding survivors in disaster scenarios. As flying in such missions is difficult the robust estimation of an MAV's state within its environment is crucial to ensure safe operation. In indoor scenarios, cameras are one of the...