In this paper, we propose a group-sensitive multiple kernel learning (GS-MKL) method to accommodate the intra-class diversity and the inter-class correlation for object categoriza...
In this work we deal with the problem of modelling and exploiting the interaction between the processes of image segmentation and object categorization. We propose a novel framewo...
In this paper we propose a novel framework for 3D object categorization. The object is modeled it in terms of its sub-parts as an histogram of 3D visual word occurrences. We introd...
Roberto Toldo, Umberto Castellani, Andrea Fusiello
This paper proposes a novel approach for multi-view multi-pose object detection using discriminative shapebased exemplars. The key idea underlying this method is motivated by nume...
Ying Shan, Feng Han, Harpreet S. Sawhney, Rakesh K...
Object recognition has reached a level where we can identify a large number of previously seen and known objects. However, the more challenging and important task of categorizing ...