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This paper presents a novel method for the challenging task of fine-structured (FS) object segmentation. The task is formulated as a label propagation problem on an affinity graph. The proposed method has mainly three advantages. First, to enhance the completeness and connectivity of FS objects, we introduce a novel neighborhood system combining both local and nonlocal connections, with a robust scheme...
Fine-structured object segmentation is a challenging problem in object segmentation community. There are mainly two difficulties that can seriously degrade the segmentation quality: 1) insufficient interactions on fine structures due to the high demand of time and manual efforts, and 2) shrinking bias that discourages long object boundaries. To address these two issues, we develop a novel method within...
Random walks (RW) is a popular technique for object segmentation. Apart from the satisfactory performance in various applications, its most appealing advantage is the computational efficiency. However, RW often fails to produce complete and connected results in fine-structured (FS) object segmentation. To utilize the high efficiency and overcome the drawbacks in tackling FS objects, we develop a novel...
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