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Seeing Behind the Camera: Identifying the Authorship of a Photograph

机译:在相机后面看:确定照片的作者身份

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We introduce the novel problem of identifying the photographer behind a photograph. To explore the feasibility of current computer vision techniques to address this problem, we created a new dataset of over 180,000 images taken by 41 well-known photographers. Using this dataset, we examined the effectiveness of a variety of features (low and high-level, including CNN features) at identifying the photographer. We also trained a new deep convolutional neural network for this task. Our results show that high-level features greatly outperform low-level features. We provide qualitative results using these learned models that give insight into our method's ability to distinguish between photographers, and allow us to draw interesting conclusions about what specific photographers shoot. We also demonstrate two applications of our method.
机译:我们介绍了识别照片背后的摄影师的新颖问题。为了探索当前计算机视觉技术解决该问题的可行性,我们创建了一个新的数据集,其中包含41位知名摄影师拍摄的180,000张图像。使用此数据集,我们检查了各种功能(低级和高级,包括CNN功能)在识别摄影师方面的有效性。我们还为此任务训练了一个新的深度卷积神经网络。我们的结果表明,高级功能大大优于低级功能。我们使用这些学习的模型提供定性结果,从而洞察我们的方法区分摄影师的能力,并允许我们得出有关特定摄影师拍摄内容的有趣结论。我们还演示了该方法的两个应用。

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