Relative-Attributes-Zero-Shot-Learning:用于图像分类和零镜头学习的视觉相对属性的Python实现-源码

上传者: 42160398 | 上传时间: 2021-09-27 22:04:04 | 文件大小: 156KB | 文件类型: ZIP
相对属性 用于图像分类和零镜头学习的视觉相对属性的Python实现 描述 此实现引用论文“ Relative Attributes, D. Parikh and K. Grauman, International Conference on Computer Vision (ICCV), 2011 。 作者给出的原始代码在matlab中。 此仓库包含用于从头开始使用牛顿优化来学习相对排名功能的python代码。 使用高斯混合模型的零射击学习也是在python中实现的。 实施细节 包含使用牛顿方法的rank svm的实现。 和 分别是用于零击学习的训练和测试文件。 此实现中使用了来自'PubFig'数据集的预提取要点特征。 要训​​练新的数据集, 模块和 可用于提取要点特征。 读取学习的排名功能,预处理的数据等,并将其保存在 目录。

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