Achieving fully autonomous driving requires not only understanding the current surrounding
conditions but also predicting how objects that could lead to potential risks may change in …

Blind area has plagued drivers' safety ever since the dawn of automobiles. Thanks to the fast-
growing vision-based perception technologies, autonomous driving systems can monitor the …

We present a method for estimating free spaces and obstacles in blind spots occluded from
a single view. Knowledge about blind spots helps autonomous vehicles make better …

Autonomous driving is currently a very active research area with virtually all automotive
manufacturers competing to bring the first fully autonomous car to the market. This race …

This study aims to enable the prediction of objects appearing from blind spots, such as
outside a field-of-view and regions occluded by other objects. Conventional prediction …

This paper introduces blind spot monitoring for vehicles using vehicle mounted cameras in
order to reduce traffic accidents. We firstly describe how intelligent surveillance can be used …

Visual environment perception is one of the key elements for autonomous and manual
driving. Modern fully automated vehicles are equipped with a range of different sensors and …

Deep Learning has seen an unprecedented increase in vision applications since the
publication of large-scale object recognition datasets and introduction of scalable compute …

High-precision maps are widely applied in intelligent-driving vehicles for localization and
planning tasks. The vision sensor, especially monocular cameras, has become favoured in …

In this paper, we introduce a method for estimating blind spots for sensor setups of
autonomous or automated vehicles and/or robotics applications. In comparison to previous …