Summary of MuSe 2020: Multimodal Sentiment Analysis, Emotion-target Engagement and Trustworthiness Detection in Real-life Media

Abstract

The first Multimodal Sentiment Analysis in Real-life Media (MuSe) 2020 was a Challenge-based Workshop held in conjunction with ACM Multimedia'20. It addresses three distinct 'in-the-wild' Sub-challenges: sentiment/ emotion recognition (MuSe-Wild), emotion-target engagement (MuSe-Target) and trustworthiness detection (MuSe-Trust). A large multimedia dataset MuSe-CaR was used, which was specifically designed with the intention of improving machine understanding approaches of how sentiment (e.g. emotion) is linked to a topic in emotional, user-generated reviews. In this summary, we describe the motivation, first of its kind 'in-the-wild' database, challenge conditions, participation, as well as giving an overview of utilised state-of-the-art techniques.