Although extensive research has been carried out to evaluate the
effectiveness of AI tools and models in detecting deep fakes, the question
remains unanswered regarding whether these models can accurately identify
genuine images that appear artificial. In this study, as an initial step
towards addressing this issue, we have curated a dataset of 510 genuine images
that exhibit a fake appearance and conducted an assessment using two AI models.
We show that two models exhibited subpar performance when applied to our
dataset. Additionally, our dataset can serve as a valuable tool for assessing
the ability of deep learning models to comprehend complex visual stimuli. We
anticipate that this research will stimulate further discussions and
investigations in this area. Our dataset is accessible at
this https URL

通过评估 AI 工具和模型在检测深度伪造方面的有效性，该研究研究了这些模型是否能够准确识别看起来人工制作的真实图像。通过创建一个包含 510 个具有虚假外观的真实图像的数据集，并使用两种 AI 模型进行评估。研究结果显示，这两个模型在我们的数据集上表现不佳。此外，我们的数据集可以作为评估深度学习模型理解复杂视觉刺激能力的有价值工具。我们期望这项研究将在该领域激发进一步的讨论和研究。我们的数据集可以在此 https 网址上获取。