Broadly, the aim of ManyFaces is to improve, diversify, and crowdsource key aspects of face research, including perception and recognition. This involves, for example, the collection and use of face stimuli; sharing existing stimulus sets; standardising stimulus collection procedures; and organising stimulus collection across multiple labs to obtain larger and more diverse face stimulus sets. ManyFaces also aims to crowdsource data collection across our members’ labs to test key research questions in face perception and recognition, enabling larger-scale designs and more diverse participant samples and generalisable findings. Finally, we aim to organise training workshops for key methods (e.g., morphing) and analyses (e.g., mixed effects models) used in face research.
