We present a framework for computing optimal transformations, aligning one point set to another, in the presence of outliers. Example applications include shape matching and regis...
The required amount of labeled training data for object detection and classification is a major drawback of current methods. Combining labeled and unlabeled data via semisupervise...
We demonstrate how to exploit reflections for accurate registration of shiny objects: The lighting environment can be retrieved from the reflections under a distant illumination a...
Pascal Lagger, Mathieu Salzmann, Vincent Lepetit, ...
We propose an approach for learning visual models of object categories in an unsupervised manner in which we first build a large-scale complex network which captures the interacti...
We present a method for learning discriminative linear feature extraction using independent tasks. More concretely, given a target classification task, we consider a complementary...