We address the problem of weakly supervised semantic segmentation. The training images are labeled only by the classes they contain, not by their location in the image. On test im...
Alexander Vezhnevets, Vittorio Ferrari, Joachim M....
Abstract. Analyzing the crowd dynamics from video sequences is an open challenge in computer vision. Under a high crowd density assumption, we characterize the dynamics of the crow...
We present a connectionist method for representing images that explicitlyaddresses their hierarchicalnature. It blends data fromneuroscience about whole-object viewpoint sensitive...
The aim of motion detection is to decide whether a given part of an image belongs to a moving object or to the static background. This paper proposes an automatic decision rule for...
We propose a method to learn heterogeneous models of object classes for visual recognition. The training images contain a preponderance of clutter and learning is unsupervised. Ou...