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Group saliency propagation for large scale and quick image co-segmentation | IEEE Conference Publication | IEEE Xplore

Group saliency propagation for large scale and quick image co-segmentation

Publisher: IEEE

Abstract:

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. The...View more

Abstract:

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 the entire group. In addition, it is also shown how a pool of these group saliency maps can help in quickly segmenting new input images. Experiments demonstrate that the proposed method can achieve competitive performance on several benchmark co-segmentation datasets including ImageNet, with the added advantage of speed up.
Date of Conference: 27-30 September 2015
Date Added to IEEE Xplore: 10 December 2015
ISBN Information:
Publisher: IEEE
Conference Location: Quebec City, QC, Canada

References

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