1. A method for learning visual attribute labels for images comprising: from textual comments associated with a corpus of images, identifying a set of candidate textual labels that are predictive of aesthetic scores associated with images in the corpus; clustering the candidate labels in the set into a plurality of visual attribute clusters based on similarity and assigning each of the clusters a visual attribute label; for each of the visual attribute labels, training a classifier using visual representations of images in the corpus and respective visual attribute labels; evaluating the visual attribute labels based on performance of the trained classifier; and retaining a subset of the visual attribute labels based on the evaluation; wherein at least one of the identifying a set of candidate textual labels, clustering the candidate labels, training the classifier, and evaluating the classifier performance is performed with a processor.