What makes you, you? Analyzing Recognition by Swapping Face Parts

. In this paper, we propose to swap facial parts as a way to disentangle the recognition relevance of different face parts, like eyes, nose and mouth. In our method, swapping parts from a source face to a target one is performed by fitting a 3D prior, which establishes dense pixels correspondence between parts, while also handling pose differences. Seamless cloning is then used to obtain smooth transitions between the mapped source regions and the shape and skin tone of the target face. We devised an experimental protocol that allowed us to draw some preliminary conclusions when the swapped images are classified by deep networks, indicating a prominence of the eyes and eyebrows region. Download paper here

Code can be found at this GitHub link.

If you find our work useful, please cite us:

@inproceedings{ferrari2022makes,
title={What makes you, you? Analyzing Recognition by Swapping Face Parts},
author={Ferrari, Claudio and Serpentoni, Matteo and Berretti, Stefano and Del Bimbo, Alberto},
booktitle={2022 26th International Conference on Pattern Recognition (ICPR)},
pages={945–951},
year={2022},
organization={IEEE}}