face-analysis/emonet
Official implementation of the paper "Estimation of continuous valence and arousal levels from faces in naturalistic conditions", Antoine Toisoul, Jean Kossaifi, Adrian Bulat, Georgios Tzimiropoulos and Maja Pantic, Nature Machine Intelligence, 2021
This project helps you automatically analyze human emotions from facial expressions in images and videos. It takes a facial image or video as input and outputs the emotional state (like happy, sad, or angry) along with continuous measures of valence (how pleasant an emotion is) and arousal (how intense it is). This would be useful for researchers studying human behavior, market analysts gauging reactions to content, or anyone needing to quantify emotional responses from visual data.
347 stars. No commits in the last 6 months.
Use this if you need to objectively analyze and quantify emotions from faces in a variety of real-world visual content.
Not ideal if you need to analyze emotions from non-facial cues like body language or vocal tone, or if you require real-time, low-latency deployment in a production system without further optimization.
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347
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Language
Python
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Last pushed
Aug 24, 2024
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