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Co-saliency detection aims at discovering the common salient objects existing in multiple images. Most existing methods combine multiple saliency cues based on fixed weights, and ignore the intrinsic relationship of these cues. In this paper, we provide a general saliency map fusion framework, which exploits the relationship of multiple saliency cues and obtains the self-adaptive weight to generate...
Co-saliency is the common saliency existing in multiple images, which keeps consistent in saliency maps. One saliency detection method generates saliency maps for all the input images, so that we have a group of maps. Salient region of each image is extracted by its corresponding saliency map in the group. We use a matrix to combine all the salient regions. Ideally, these co-salient regions are similar...
High-level visual recognition such as scene classification is a challenging task in computer vision. In this paper, we propose an image descriptor based on semantic cliques obtained by high-order pure dependence, and the image is represented by a vector whose element denotes the probability of containing each object cliques. Compared with using single objects as attributes, such representation carries...
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