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Titlebook: Computer Vision –ACCV 2016; 13th Asian Conferenc Shang-Hong Lai,Vincent Lepetit,Yoichi Sato Conference proceedings 2017 Springer Internatio

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11#
發(fā)表于 2025-3-23 10:42:46 | 只看該作者
A Holistic Approach for Data-Driven Object Cutoutn an instance of the class, and further process good proposals to produce an accurate object cutout mask. This amounts to an automatic end-to-end pipeline for catergory-specific object cutout. We evaluate our approach on segmentation benchmark datasets, and show that it significantly outperforms the
12#
發(fā)表于 2025-3-23 16:14:33 | 只看該作者
Interactive Segmentation from 1-Bit Feedbackrence. Over-segmentation reduces the solution set of questions and the computational costs of transductive inference. Entropy calculation provides a way to characterize the query order of superpixels. Transductive inference is used to estimate the similarity between superpixels and to partition the
13#
發(fā)表于 2025-3-23 19:32:02 | 只看該作者
14#
發(fā)表于 2025-3-24 01:41:14 | 只看該作者
Socialism and Boulangism, 1887–89accelerate the pixel-wise learning stage. Then, trimap skeleton based algorithm is proposed to divide the image into blocks and process blocks in parallel to speed up the solving stage. Experimental results demonstrated that the proposed scheme achieves a maximal 12+ speedup over previous serial methods without degrading segmentation precision.
15#
發(fā)表于 2025-3-24 06:05:19 | 只看該作者
Parallel Accelerated Matting Method Based on Local Learningaccelerate the pixel-wise learning stage. Then, trimap skeleton based algorithm is proposed to divide the image into blocks and process blocks in parallel to speed up the solving stage. Experimental results demonstrated that the proposed scheme achieves a maximal 12+ speedup over previous serial methods without degrading segmentation precision.
16#
發(fā)表于 2025-3-24 07:28:05 | 只看該作者
The Development of the Laboratory structures into a segmentation hierarchy with explicitly imposed containment of lower level supervoxels in higher level supervoxels. Comparisons are conducted against state of the art 3D segmentation algorithms. The considered applications are 3D spatial and 2D spatiotemporal segmentation scenarios.
17#
發(fā)表于 2025-3-24 13:23:48 | 只看該作者
18#
發(fā)表于 2025-3-24 16:29:37 | 只看該作者
19#
發(fā)表于 2025-3-24 23:03:30 | 只看該作者
20#
發(fā)表于 2025-3-25 00:09:57 | 只看該作者
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