While lots of people may think branding begins and ends with a logo, fashion brands communicate their uniqueness through a wide range of visual cues such as color, patterns and shapes. In this work, we analyze learned visual representations by deep networks that are trained to recognize fashion brands. In particular, the activation strength and extent of neurons are studied to provide interesting insights about visual brand expressions. The proposed method identifies where a brand stands in the spectrum of branding strategy, i.e., from trademark-emblazoned goods with bold logos to implicit no logo marketing. By quantifying attention maps, we are able to interpret the visual characteristics of a brand present in a single image and model the general design direction of a brand as a whole. We further investigate versatility of neurons and discover "specialists" that are highly brand-specific and "generalists" that detect diverse visual features. A human experiment based on three main visual scenarios of fashion brands is conducted to verify the alignment of our quantitative measures with the human perception of brands. This paper demonstrate how deep networks go beyond logos in order to recognize clothing brands in an image.

本文提出了一种基于深度神经网络的品牌视觉识别方法，通过对神经元的激活程度和范围进行研究，来解释和量化品牌视觉表达的特征和整体设计方向，其中包括品牌策略的各种变化，并且利用定量测量方法验证了该方法与人类对品牌视觉感知的一致性。

品牌 > 标志：时尚品牌的视觉分析