This work provides a framework for learning sequential attention in real-world visual object recognition, using an architecture of three processing stages. The first stage rejects...
We investigate the challenging issue of joint audio-visual analysis of generic videos targeting at semantic concept detection. We propose to extract a novel representation, the Sh...
Wei Jiang, Courtenay V. Cotton, Shih-Fu Chang, Dan...
We show that the discrimination between visually similar classes often depends on the detection of socalled ‘satellite features’. These are local features which are not inform...
In this paper, we propose a scheme to improve the performance of subspace learning by using a pattern(data) selection method as preprocessing. Generally, a training set for subspa...
Jin Hee Na, Seok Min Yun, Minsoo Kim, Jin Young Ch...
Abstract This work introduces a self-supervised architecture for robust classification of moving obstacles in urban environments. Our approach presents a hierarchical scheme that r...
Roman Katz, Juan Nieto, Eduardo Mario Nebot, Bertr...