— A novel framework to context modeling, based on the probability of co-occurrence of objects and scenes is proposed. The modeling is quite simple, and builds upon the availabili...
We address the problem of learning object class models and object segmentations from unannotated images. We introduce LOCUS (Learning Object Classes with Unsupervised Segmentation...
In this paper, we investigate what can be inferred from several silhouette probability maps, in multi-camera environments. To this aim, we propose a new framework for multi-view s...
View identification is the basal process for solid reconstruction from engineering drawings. A new method is presented to label various views from a section-involved drawing and i...
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...