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Most existing high-performance co-segmentation algorithms are usually complex due to the way of co-labeling a set of images as well as the common need of fine-tuning few parameters for effective co-segmentation. In this paper, instead of following the conventional way of co-labeling multiple images, we propose to first exploit inter-image information through co-saliency, and then perform single-image...
Most of the existing co-segmentation methods are usually complex, and require pre-grouping of images, fine-tuning a few parameters and initial segmentation masks etc. These limitations become serious concerns for their application on large scale datasets. In this paper, Group Saliency Propagation (GSP) model is proposed where a single group saliency map is developed, which can be propagated to segment...
Most existing high-performance co-segmentation algorithms are usually complicated due to the way of co-labelling a set of images and the requirement to handle quite a few parameters for effective co-segmentation. In this paper, instead of relying on the complex process of co-labelling multiple images, we perform segmentation on individual images but based on a combined saliency map that is obtained...
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