Keynote lecture 1: "Visual scene understanding — It´s time to address it again"

Summary form only given. Inspired by the ability of humans to interpret and understand 3D scenes nearly effortlessly, the problem of 3D scene understanding has long been advocated as the "holy grail" of computer vision. In the early days this problem was addressed in a bottom-up fashion without enabling satisfactory or reliable results for scenes of realistic complexity. In recent years there has been considerable progress on many sub-problems of the overall 3D scene understanding problem. As the performance for these sub-tasks starts to achieve remarkable performance levels, we argue that the problem to automatically infer and understand 3D scenes should be addressed again. In this talk we will - on the one hand - highlight progress on some essential components of scene understanding such as object class recognition and articulated pose estimation and tracking. On the other hand, we will also report on our current attempt towards 3D scene understanding in the particular case of traffic scene analysis.