Accurately and precisely delineating road-markings from very high spatial resolution
unmanned aerial vehicle (UAV) images face many challenges, such as complex scenarios …

Aiming at the low detection accuracy and poor positioning for small objects of single-stage
object detection algorithms, we improve the backbone network of SSD (Single Shot MultiBox …

Autonomous driving systems have emerged with the promise of preventing accidents. The
first critical aspect of these systems is perception, where the regular practice is the use of top …

Building extraction has attracted considerable attention in the field of remote sensing image
analysis. Fully convolutional network modelling is a recently developed technique that is …

High-definition (HD) map serves as the essential infrastructure of autonomous driving. In this
work, we build up a systematic vectorized map annotation framework (termed VMA) for …

In this paper, we focus on the problem of contextual aggregation in the semantic
segmentation of aerial images. Current contextual aggregation methods only aggregate …

Aerial pixel-wise scene perception of the surrounding environment is an important task for
UAVs (Unmanned Aerial Vehicles). Previous research works mainly adopt conventional …

Classification of aerial imagery is essential for water channel surveillance and waterfront
land cover characterization. It is also beneficial to long-duration collaborative autonomous …

Safe roads are a necessity for any society because of the high social costs of traffic
accidents. This challenge is addressed by a novel methodology that allows us to evaluate …

The upraise of autonomous driving technologies asks for maps characterized bya broad
range of features and quality parameters, in contrast to traditional navigation maps which in …