Nearly every structured prediction problem in computer vision requires approximate inference due to large and complex dependencies among output labels. While graphical models prov...
We propose a non-linear graphical model for structured prediction. It combines the power of deep neural networks to extract high level features with the graphical framework of Mar...
— In this paper, motivated by the goal of modeling the fine-grain capabilities of jammers for the context of security in low-power wireless networks, we experimentally character...
We present a new local method for collision avoidance that is based on collision prediction. In our model, each pedestrian predicts possible future collisions with other pedestrian...
Ioannis Karamouzas, Peter Heil, Pascal van Beek, M...
In this paper, we consider the problem of determining feature saliency for 3D objects and describe a series of experiments that examined if salient features exist and can be predi...