Many studies of visual working memory have tested humans' ability to reproduce primary visual features of simple objects, such as the orientation of a grating or the hue of a color patch, following a delay. A consistent finding of such studies is that precision of responses declines as the number of items in memory increases. Here we compared visual working memory for primary features and high-level objects. We presented participants with memory arrays consisting of oriented gratings, facial expressions, or a mixture of both. Precision of reproduction for all facial expressions declined steadily as the memory load was increased from one to five faces. For primary features, this decline and the specific distributions of error observed, have been parsimoniously explained in terms of neural population codes. We adapted the population coding model for circular variables to the non-circular and bounded parameter space used for expression estimation. Total population activity was held constant according to the principle of normalization and the intensity of expression was decoded by drawing samples from the Bayesian posterior distribution. The model fit the data well, showing that principles of population coding can be applied to model memory representations at multiple levels of the visual hierarchy. When both gratings and faces had to be remembered, an asymmetry was observed. Increasing the number of faces decreased precision of orientation recall, but increasing the number of gratings did not affect recall of expression, suggesting that memorizing faces involves the automatic encoding of low-level features, in addition to higher-level expression information.