Abstract

We introduce the novel problem of identifying the pho-tographer behind a photograph. To explore the feasibility ofcurrent 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 ex-amined 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 in-sight 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.