This paper explores the power and the limitations of weakly supervised categorization. We present a complete framework that starts with the extraction of various local regions of e...
Andreas Opelt, Axel Pinz, Michael Fussenegger, Pet...
We present a novel boosting algorithm where temporal consistency is addressed in a short-term way. Although temporal correlation of observed data may be an important cue for classi...
Pedro Canotilho Ribeiro, Plinio Moreno, José...
Abstract. A new approach, called Collective Shape Difference Classifier (CSDC), is proposed to improve the accuracy and computational efficiency of 3D face recognition. The CSDC le...
Yueming Wang, Xiaoou Tang, Jianzhuang Liu, Gang Pa...
We propose to use binary strings as an efficient feature point descriptor, which we call BRIEF. We show that it is highly discriminative even when using relatively few bits and can...
Abstract. This paper proposes a new approach to learning a discriminative model of object classes, incorporating appearance, shape and context information efficiently. The learned ...
Jamie Shotton, John M. Winn, Carsten Rother, Anton...