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arXiv · 1805.00833

Learnable PINs: Cross-Modal Embeddings for Person Identity

Arsha Nagrani·Samuel Albanie·Andrew Zisserman
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Abstract

We propose and investigate an identity sensitive joint embedding of face and voice. Such an embedding enables cross-modal retrieval from voice to face and from face to voice. We make the following four contributions: first, we show that the embedding can be learnt from videos of talking faces, without requiring any identity labels, using a form of cross-modal self-supervision; second, we develop a curriculum learning schedule for hard negative mining targeted to this task, that is essential for learning to proceed successfully; third, we demonstrate and evaluate cross-modal retrieval for identities unseen and unheard during training over a number of scenarios and establish a benchmark for this novel task; finally, we show an application of using the joint embedding for automatically retrieving and labelling characters in TV dramas.

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Arsha Nagrani, Samuel Albanie, Andrew Zisserman. 2018-05-02. Learnable PINs: Cross-Modal Embeddings for Person Identity. https://arxiv.org/abs/1805.00833

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