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MDNS facial expression perception dataset

De'Aira Bryant, Tiffany Deng, Nashlie Sephus, Wei Xia, Pietro Perona
2022
Last updated November 22, 2023
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This project is credited to De'Aira Bryant's internship project at Amazon AWS.

Humans can perceive multiple expressions in a single face. Such expressions may also be perceived at varying intensities. By coupling annotations from multiple observers, it can be observed that some expressions are also ambiguous. The MDNS (multi-dimensional, nuanced, subjective) annotation dataset provides a new set of multi-dimensional modulated annotations for 1000 face images. The images were sourced from the standard ExpW face image dataset. This novel in-the-wild, ethnically diverse dataset been annotated along 6, 15, and 21 expression dimensions by multiple crowd-sourced annotators. Here, we provide the raw annotator ratings and demonstrate a probabilistic technique that can be used to model human perception.

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