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DC Field | Value | Language |
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dc.contributor.author | Dhall, A. | - |
dc.contributor.author | Singh, M. | - |
dc.contributor.author | Goecke, R. | - |
dc.contributor.author | Gedeon, T. | - |
dc.contributor.author | Zemg, D. | - |
dc.contributor.author | Wang, Y. | - |
dc.contributor.author | Ikeda, K. | - |
dc.date.accessioned | 2024-05-20T13:23:49Z | - |
dc.date.available | 2024-05-20T13:23:49Z | - |
dc.date.issued | 2024-05-20 | - |
dc.identifier.uri | http://dspace.iitrpr.ac.in:8080/xmlui/handle/123456789/4526 | - |
dc.description.abstract | This paper describes the 9th Emotion Recognition in the Wild (EmotiW) challenge, which is being run as a grand challenge at the 25th ACM International Conference on Multimodal Interaction 2023. EmotiW challenge focuses on afect related benchmarking tasks and comprises of two sub-challenges: a) User Engagement Prediction in the Wild, and b) Audio-Visual Group-based Emotion Recognition. The purpose of this challenge is to provide a common platform for researchers from diverse domains. The objective is to promote the development and assessment of methods, which can predict engagement levels and/or identify perceived emotional well- being of a group of individuals in real-world circumstances. We describe the datasets, the challenge protocols and the accompanying sub-challenge. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | Afective Computing | en_US |
dc.subject | Group Emotions | en_US |
dc.subject | Engagement | en_US |
dc.title | EmotiW 2023: Emotion Recognition in the Wild Challenge | en_US |
dc.type | Article | en_US |
Appears in Collections: | Year-2023 |
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full text.pdf | 452.58 kB | Adobe PDF | View/Open Request a copy |
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