Abstract | ||
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Personality and emotion are both central to affective computing. Existing works address them individually. In this demo we investigate if such high-level affect traits and their relationship can be jointly learned from face images in the wild. To this end, we introduce an end-to-end trainable and deep Siamese-like network. At inference time, our system can take one portrait photo as input and predict one's Big-Five apparent personality as well as emotion attributes. With such a system, we also demonstrate the feasibility of inferring the apparent personality directly fro emotion.
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Year | DOI | Venue |
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2018 | 10.1145/3240508.3241384 | MM '18: ACM Multimedia Conference
Seoul
Republic of Korea
October, 2018 |
Keywords | Field | DocType |
Personality, Emotion, Emotion-to-Personality, Deep Learning | Inference,Computer science,Portrait,Cognitive psychology,Artificial intelligence,Affective computing,Deep learning,Multimedia,Personality | Conference |
ISBN | Citations | PageRank |
978-1-4503-5665-7 | 1 | 0.35 |
References | Authors | |
5 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Songyou Peng | 1 | 24 | 4.57 |
Le Zhang | 2 | 268 | 32.16 |
Stefan Winkler | 3 | 3 | 0.74 |
Marianne Winslett | 4 | 3519 | 744.78 |