The article introduces the concept of image ``culturization," i.e., defined as the process of altering the ``brushstroke of cultural features" that make objects perceived as belonging to a given culture while preserving their functionalities. First, we defined a pipeline for translating objects' images from a source to a target cultural domain based on state-of-the-art Generative Adversarial Networks. Then, we gathered data through an online questionnaire to test four hypotheses concerning the impact of images belonging to different cultural domains on Italian participants. As expected, results depend on individual tastes and preferences: however, they align with our conjecture that some people, during the interaction with an intelligent system, will prefer to be shown images modified to match their cultural background.

翻译：本文引入了图像“文化化”的概念，即定义为改变“文化特征笔触”的过程，这些笔触使物体感知为属于特定文化，同时保留其功能。首先，我们基于最先进的生成对抗网络，定义了一个将物体图像从源文化域翻译到目标文化域的流程。然后，我们通过在线问卷收集数据，以检验四项假设，这些假设涉及属于不同文化域的图像对意大利参与者的影响。正如预期，结果取决于个人品味和偏好：然而，它们与我们的猜想一致，即一些人在与智能系统交互过程中，更倾向于看到被修改以匹配其文化背景的图像。