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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(More)
Co-saliency aims at detecting common saliency in a series of images, which is useful for a variety of multimedia applications. In this paper, we address the co-saliency detection to a reconstruction problem: the foreground could be well reconstructed by using the reconstruction bases, which are extracted from each image and have the similar appearances in(More)
Plastic film mulching (PM) has been widely used to improve maize (Zea mays L.) yields and water use efficiency (WUE) in Northeast China, but the effects of PM in a changing climate characterized by highly variable precipitation are not well understood. Six site-year field experiments were conducted in the dry and rainy years to investigate the effects of PM(More)
Visual saliency has been widely used in many applications. However, the performance of an individual saliency detection method varies with the different images. Integrating multiple methods together could compensate this shortcoming, and thus is expected to improve the performance of saliency detection. In this paper, we present an unsupervised(More)