VEMOCLAP: A video emotion classification web application

VEMOCLAP: A video emotion classification web application

We introduce VEMOCLAP: Video EMOtion Classifier using Pretrained features, the first readily available and open-source web application that analyzes the emotional content of any user-provided video. We improve our previous work, which exploits open-source pretrained models that work on video frames...

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Hauptverfasser: Sulun, Serkan, Viana, Paula, Davies, Matthew E. P
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Computer Science - Artificial Intelligence
Computer Science - Computer Vision and Pattern Recognition
Computer Science - Learning
Computer Science - Multimedia
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creator Sulun, Serkan
Viana, Paula
Davies, Matthew E. P
description We introduce VEMOCLAP: Video EMOtion Classifier using Pretrained features, the first readily available and open-source web application that analyzes the emotional content of any user-provided video. We improve our previous work, which exploits open-source pretrained models that work on video frames and audio, and then efficiently fuse the resulting pretrained features using multi-head cross-attention. Our approach increases the state-of-the-art classification accuracy on the Ekman-6 video emotion dataset by 4.3% and offers an online application for users to run our model on their own videos or YouTube videos. We invite the readers to try our application at serkansulun.com/app.
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Computer Science - Computer Vision and Pattern Recognition
Computer Science - Learning
Computer Science - Multimedia
title VEMOCLAP: A video emotion classification web application
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