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Hierarchical classification is a computational efficient approach for large-scale image classification. The main challenging issue of this approach is to deal with error propagation. Irrelevant branching decision made at a parent node cannot be corrected at its child nodes in traversing the tree for classification. This paper presents a novel approach to reduce branching error at a node by taking...
We study the problem of multi-class image classification with large number of classes, of which the one-vs-all based approach is prohibitive in practical applications. Recent state-of-the-art approaches rely on label tree to reduce classification complexity. However, building optimal tree structures and learning precise classifiers to optimize tree loss is challenging. In this paper, we introduce...
Action recognition has been an important and challenging task in computer vision. Existing approaches usually employ pooling operation to encode isolated patches or trajectories and then aggregate them for a compact video presentation. In this paper, we make two contributions towards improving action recognition accuracy and efficiency. First, we study to apply a state-of-the-art pooling technique...
Video shot boundary detection is one of the fundamental tasks of video indexing and retrieval applications. Although many methods have been proposed for this task, finding a general and robust shot boundary method that is able to handle the various transition types caused by photo flashes, rapid camera movement and object movement is still challenging. We present a novel approach for detecting video...
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