A Survey of Deep Learning for Group-level Emotion Recognition Article Swipe

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Xiaohua Huang , Jinke Xu , Wenming Zheng , Qirong Mao , Abhinav Dhall ·

YOU? · · 2024 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2408.15276

With the advancement of artificial intelligence (AI) technology, group-level emotion recognition (GER) has emerged as an important area in analyzing human behavior. Early GER methods are primarily relied on handcrafted features. However, with the proliferation of Deep Learning (DL) techniques and their remarkable success in diverse tasks, neural networks have garnered increasing interest in GER. Unlike individual's emotion, group emotions exhibit diversity and dynamics. Presently, several DL approaches have been proposed to effectively leverage the rich information inherent in group-level image and enhance GER performance significantly. In this survey, we present a comprehensive review of DL techniques applied to GER, proposing a new taxonomy for the field cover all aspects of GER based on DL. The survey overviews datasets, the deep GER pipeline, and performance comparisons of the state-of-the-art methods past decade. Moreover, it summarizes and discuss the fundamental approaches and advanced developments for each aspect. Furthermore, we identify outstanding challenges and suggest potential avenues for the design of robust GER systems. To the best of our knowledge, thus survey represents the first comprehensive review of deep GER methods, serving as a pivotal references for future GER research endeavors.

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Psychology Group (periodic table) Emotion recognition Cognitive psychology Chemistry Neuroscience Organic chemistry

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Type: preprint
Language: en
Landing Page: http://arxiv.org/abs/2408.15276
PDF: https://arxiv.org/pdf/2408.15276
OA Status: green
Related Works: 10
OpenAlex ID: https://openalex.org/W4402703221

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DOI: https://doi.org/10.48550/arxiv.2408.15276

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Title: A Survey of Deep Learning for Group-level Emotion Recognition

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Type: preprint

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Language: en

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Publication year: 2024

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Publication date: 2024-08-13

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Authors: Xiaohua Huang, Jinke Xu, Wenming Zheng, Qirong Mao, Abhinav Dhall

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Landing page: https://arxiv.org/abs/2408.15276

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PDF URL: https://arxiv.org/pdf/2408.15276

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Concepts: Psychology, Group (periodic table), Emotion recognition, Cognitive psychology, Chemistry, Neuroscience, Organic chemistry

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