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DC Field | Value | Language |
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dc.contributor.author | Dhall, A. | - |
dc.contributor.author | Sharma, G. | - |
dc.contributor.author | Goecke, R. | - |
dc.contributor.author | Gedeon, T. | - |
dc.date.accessioned | 2021-07-02T00:05:31Z | - |
dc.date.available | 2021-07-02T00:05:31Z | - |
dc.date.issued | 2021-07-02 | - |
dc.identifier.uri | http://localhost:8080/xmlui/handle/123456789/1961 | - |
dc.description.abstract | This paper introduces the Eighth Emotion Recognition in the Wild (EmotiW) challenge. EmotiW is a benchmarking effort run as a grand challenge of the 22nd ACM International Conference on Multimodal Interaction 2020. It comprises of four tasks related to automatic human behavior analysis: a) driver gaze prediction; b) audio-visual group-level emotion recognition; c) engagement prediction in the wild; and d) physiological signal based emotion recognition. The motivation of EmotiW is to bring researchers in affective computing, computer vision, speech processing and machine learning to a common platform for evaluating techniques on a test data. We discuss the challenge protocols, databases and their associated baselines. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | Affective computing | en_US |
dc.subject | automatic human behavior analysis | en_US |
dc.subject | group emotions | en_US |
dc.subject | driver gaze prediction | en_US |
dc.subject | student engagement | en_US |
dc.title | EmotiW 2020: driver gaze, group emotion, student engagement and physiological signal based challenges | en_US |
dc.type | Article | en_US |
Appears in Collections: | Year-2020 |
Files in This Item:
File | Description | Size | Format | |
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Fulltext.pdf | 5.3 MB | Adobe PDF | View/Open Request a copy |
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