We present a probabilistic framework for recognizing objects in images of cluttered scenes. Hundreds of objects may be considered and searched in parallel. Each object is learned f...
This paper presents an image editing framework where users use reference images to indicate desired color edits. In our approach, users specify pairs of strokes to indicate corres...
Real-time tessellation methods offer the ability to upsample 3D surface meshes on the fly during rendering. This upsampling relies on 3 major steps. First, it requires a tessellat...
Augmented reality applications often rely on a detailed environment model to support features such as annotation and occlusion. Usually, such a model is constructed offline, whic...
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....