Random Forests (RFs) have become commonplace
in many computer vision applications. Their
popularity is mainly driven by their high computational
efficiency during both training ...
Christian Leistner, Amir Saffari, Jakob Santner, H...
Video-based recognition and prediction of a temporally extended activity can benefit from a detailed description of high-level expectations about the activity. Stochastic grammars...
Autonomous cars will likely play an important role in the future. A vision system designed to support outdoor navigation for such vehicles has to deal with large dynamic environme...
Many problems in vision involve the prediction of a class label for each frame in an unsegmented sequence. In this paper, we develop a discriminative framework for simultaneous se...
We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...