Recent years have witnessed enormous progress in AI-related fields such as computer
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …

3D semantic scene labeling is fundamental to agents operating in the real world. In
particular, labeling raw 3D point sets from sensors provides fine-grained semantics. Recent …

Complex structures commonly exist in natural images. When an image contains small-scale
high-contrast patterns either in the background or foreground, saliency detection could be …

Our abilities in scene understanding, which allow us to perceive the 3D structure of our
surroundings and intuitively recognise the objects we see, are things that we largely take for …

Stereo techniques have witnessed tremendous progress over the last decades, yet some
aspects of the problem still remain challenging today. Striking examples are reflecting and …

Autonomous driving is a key factor for future mobility. Properly perceiving the environment of
the vehicles is essential for a safe driving, which requires computing accurate geometric and …

Efficient and effective multisensor fusion techniques are demanded in order to fully exploit
two complementary data modalities, eg aerial optical imagery, and the LiDAR data. Recent …

This paper addresses the task of designing a modular neural network architecture that jointly
solves different tasks. As an example we use the tasks of depth estimation and semantic …

Given a picture taken somewhere in the world, automatic geo-localization of such an image
is an extremely useful task especially for historical and forensic sciences, documentation …

Blockchain shows a huge prospective in the coming future. It is atechnology that provides
the possibility of generating and sharing transaction ledgers that are tamper proof. Use …