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Semantic-Segmentation CVPR2012_oral Weakly Supervised Structured Output Learning for Special Effects 图形图像处理 238万源代码下载- www.pudn.com
 文件名称: Semantic-Segmentation下载   收藏√  [投票:非常好  5  4  3  2  1 投票:太差了]
  所属分类: Special Effects
  开发工具: PDF
  文件大小: 2149 KB
  上传时间: 2012-12-06
  下载次数: 6
  提 供 者: 费炳超
 详细说明:CVPR2012_oral Weakly Supervised Structured Output Learning for Semantic Segmentation-We address the problem of weakly supervised semantic segmentation. The training images are labeled only by the classes they contain, not by their location in the image. On test images instead, the method must predict a class label for every pixel. Our goal is to enable segmentation algorithms to use multiple visual cues in this weakly supervised setting, analogous to what is achieved by fully supervised methods. However, it is difficult to assess the relative usefulness of different visual cues from weakly supervised training data. We define a parametric family of structured models, where each model weighs visual cues in a different way. We propose a Maximum Expected Agreement model selection principle that evaluates the quality of a model from the family without looking at superpixel labels. Searching for the best model is a hard optimization problem, which has no analytic gradient and multiple local optima. We cast it as a Bayesian optimization problem and propose an
 近期下载过的用户:  Abirami [查看上载者费炳超的更多信息]
 相关搜索: superpixel segmentation 
 输入关键字,在本站238万海量源码库中尽情搜索:  帮助
 [MovingMultiPoints.zip] - 采用距离多普勒成像算法对运动的多点目标进行了仿真,能够更深刻地掌握成像算法
 [Gupta_CVPR12.zip] - CVPR2012_oral Micro Phase Shifting
 [InteractiveImagesegmentationbasedonMergingRegion.r] - 基于区域融合的半监督的图像分割算法。首先在背景和前景手动设置初始分割标记,在迭代过程中不断通过区域融合操作获得最大相似度的区域,从而实现目标分割。

 [SVM.rar] - 这是一个讲解机器学习与SVM的课件,讲的深入浅出,非常不错。
 [turbopixels_code.tar.gz] - 目前效果最好的超像素分割代码,采用水平集演化方法。