The use of computer-generated (CG) stimuli in face processing research is proliferating due to the ease with which faces can be generated, standardised and manipulated. However there has been surprisingly little research into whether CG faces are processed in the same way as photographs of real faces. The present study assessed how well CG faces tap face identity expertise by investigating whether two indicators of face expertise are reduced for CG faces when compared to face photographs. These indicators were accuracy for identification of own-race faces and the other-race effect (ORE)–the well-established finding that own-race faces are recognised more accurately than other-race faces. In Experiment 1 Caucasian and Asian participants completed a recognition memory task for own- and other-race real and CG faces. Overall accuracy for own-race faces was dramatically reduced for CG compared to real faces and the ORE was significantly and substantially attenuated for CG faces. Experiment 2 investigated perceptual discrimination for own- and other-race real and CG faces with Caucasian and Asian participants. Here again, accuracy for own-race faces was significantly reduced for CG compared to real faces. However the ORE was not affected by format. Together these results signal that CG faces of the type tested here do not fully tap face expertise. Technological advancement may, in the future, produce CG faces that are equivalent to real photographs. Until then caution is advised when interpreting results obtained using CG faces.

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Many aspects of faces derived from structural information appear to be neurally represented using norm-based opponent coding. Recently, however, Zhao, Seriès, Hancock, and Bednar (2011) have argued that another aspect with a strong structural component, namely face gender, is instead multichannel coded. Their conclusion was based on finding that face gender aftereffects initially increased but then decreased for adaptors with increasing levels of gender caricaturing. Critically, this interpretation rests on the untested assumption that caricaturing the differences between male and female composite faces increases perceived sexual dimorphism (masculinity/femininity) of faces. We tested this assumption in Study 1 and found that it held for male, but not female faces. A multichannel account cannot, therefore, be ruled out, although a decrease in realism of adaptors was observed that could have contributed to the decrease in aftereffects. However, their aftereffects likely reflect low-level retinotopic adaptation, which was not minimized for most of their participants. In Study 2 we minimized low-level adaptation and found that face gender aftereffects were strongly positively related to the perceived sexual dimorphism of adaptors. We found no decrease for extreme adaptors, despite testing adaptors with higher perceived sexual dimorphism levels than those used by Zhao et al. These results are consistent with opponent coding of higher-level dimensions related to the perception of face gender.