The thriving of online fashion markets has increasingly drawn people's attention. More and more small business owners and individual sellers have joined the traditional professional retail industry, which has led to the blooming of image-based online fashion communities and product photography. Accordingly, we have been dedicated to study how to improve the aesthetic quality of fashion images. In previous work, based on the psychophysical experiments we conducted and the aesthetics evaluation of a given collection of photos, we designed features for aesthetics inference, and introduced a SVM predictor to indicate the image quality. Using this predictor we investigate a large range of fashion photos; and our recent findings show that human aesthetic feedback on fashion images significantly depends on another two high-level factors: the nature of the background in the photo, and how the fashion items are displayed. We believe that fashion photos in which the fashion item is worn by a model, or placed on a mannequin are more aesthetically pleasing than others; and likewise people tend to prefer photos with white background. Furthermore, based on ground truth data that we collected, we perform a statistical analysis to validate these conclusions.