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Learning Good Taste : Classifying Aesthetic Images

When humans look at an image they not only understand the subject matter, they also make a number of subjective assessments about it such as aesthetic quality, emotional intensity, creativity, etc. In this work we attempt to classify images based on their aesthetic appeal. Much like image recognition, the features which comprise a beautiful image are difficult to describe and quantify by hand. Thus we use convolutional neural networks to automatically learn features and evaluate images. Our system is more accurate than previous systems on the same dataset.