Abstract
Representations of individual faces evolve with experience to support progressively more robust recognition. Knowledge of three-dimensional face structure is required to predict an image of a face as illumination and viewpoint change. Robust recognition across such transformations can be achieved with representations based on multiple two-dimensional views, three-dimensional structure, or both. We used face-identity adaptation in a familiarization paradigm to address a long-standing controversy concerning the role of two-dimensional versus three-dimensional information in face representations. We reasoned that if three-dimensional information is coded in the representations of familiar faces, then learning a new face using images generated by one three-dimensional transformation should enhance the robustness of the representation to another type of three-dimensional transformation. Familiarization with multiple views of faces enhanced the transfer of face-identity adaptation effects across changes in illumination by compensating for a generalization cost at a novel test viewpoint. This finding demonstrates a role for three-dimensional information in representations of familiar faces.
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