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FaceSim3D ๐Ÿ—ฟ๐Ÿ—ฟ

Testing the effect of dynamic 3D viewing conditions on face similarity perception

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Project description๐Ÿ—ฟ

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To test the effect of space and time on face similarity judgments, we conducted an online experiment using a triplet odd-one-out task in a static 2D and a dynamic 3D condition. We then trained sparse and deep computational encoding models of human face similarity judgments to investigate the latent representations that underlie their predictions.

How to navigate this project documentation?๐Ÿ—ฟ

๐Ÿ—ฟ : A brief overview of the experiment can be found in the section Experiment.

: Results are summarized in the form of a Jupyter notebook in the section Results.

: The research code is available as a Python package. For its setup and API reference, see the section Research Code.

Citation๐Ÿ—ฟ

If you use this code or data, please cite the following paper (Hofmann et al. Dynamic presentation in 3D modulates face similarity judgments. PsyArXiv. 2025):

@article{hofmannDynamicPresentation3D2025,
  title = {Dynamic presentation in {{3D}} modulates face similarity judgments -- {{A}} human-aligned encoding model approach},
  author = {Hofmann, Simon M. and Ciston, Anthony Buck and Koushik, Abhay and Klotzsche, Felix and Hebart, Martin N. and M\"uller, Klaus-Robert and Villringer, Arno and Scherf, Nico and Hilsmann, Anna and Nikulin, Vadim V. and Gaebler, Michael},
  journal = {PsyArXiv},
  doi = {10.31234/osf.io/f62pw},
  year = {2025},
}

Contributors/Collaborators๐Ÿ—ฟ

Simon M. Hofmann*, Anthony Ciston, Abhay Koushik, Felix Klotzsche, Martin N. Hebart, Klaus-Robert Mรผller, Arno Villringer, Nico Scherf, Anna Hilsmann, Vadim V. Nikulin, Michael Gaebler

This study was conducted at the Max Planck Institute for Human Cognitive and Brain Sciences as part of the NEUROHUM project.

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* corresponding author