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 visual attribute 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 visual attribute classifiers, the evaluating comprising comparing performance of each of the visual attribute classifiers with a predefined threshold; and retaining a subset of the visual attribute labels based on the evaluation, including retaining the visual attribute labels for the visual attribute classifiers that meet the performance threshold; 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.