We address the problem of multiclass object detection. Our aims are to enable models for new categories to benefit from the detectors built previously for other categories, and fo...
Abstract. We describe a system for autonomous learning of visual object representations and their grasp affordances on a robot-vision system. It segments objects by grasping and mo...
Dirk Kraft, Renaud Detry, Nicolas Pugeault, Emre B...
Traditional aspect graphs are topology-based and are impractical for articulated objects. In this work we learn a small number of aspects, or prototypical views, from video data. ...
Active learning and crowdsourcing are promising ways to efficiently build up training sets for object recognition, but thus far techniques are tested in artificially controlled ...
The segmentation problem appears in most medical imaging applications. Many research groups are pushing toward a whole body segmentation based on atlases. With a similar objective,...