所谓的中层表达就是一些服装属性。作为隐变量的SVM的隐含层结点。

To narrow the semantic gap between the low-level features of clothing and the high-level occasion categories, we adopt middle-level clothing attributes (e.g., clothing category, color, pattern) as a bridge. More specifi- cally, the clothing attributes are treated as latent variables in our proposed latent Support Vector Machine (SVM) based recommendation model.

主要目标

• 服装推荐(suggestion)
• 服装搭配(pairing)

parsing部分

• 特征
  从姿态估计的20个上身区域和10个下身区域提取5种特征，包括：HOG，LBP，color moment, 色彩直方图，肤色。
  最终生成特征每个part28770维度
• latent SVM
  (x, a u , a l , o)
  其中x为特征，au和al分别为上下半身的中层特征，即属性，作为隐变量。