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short-paper

EmotiW 2018: Audio-Video, Student Engagement and Group-Level Affect Prediction

Authors:

Tom GedeonAuthors Info & Claims

ICMI '18: Proceedings of the 20th ACM International Conference on Multimodal Interaction

Pages 653 - 656

https://doi.org/10.1145/3242969.3264993

Published: 02 October 2018 Publication History

Abstract

This paper details the sixth Emotion Recognition in the Wild (EmotiW) challenge. EmotiW 2018 is a grand challenge in the ACM International Conference on Multimodal Interaction 2018, Colarado, USA. The challenge aims at providing a common platform to researchers working in the affective computing community to benchmark their algorithms on 'in the wild' data. This year EmotiW contains three sub-challenges: a) Audio-video based emotion recognition; b) Student engagement prediction; and c) Group-level emotion recognition. The databases, protocols and baselines are discussed in detail.

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Cited By

Tao HLiu CLiu Y(2024)A study on automatic identification of students’ emotional states using convolutional neural networksApplied Mathematics and Nonlinear Sciences10.2478/amns-2024-34309:1Online publication date: 25-Nov-2024
https://doi.org/10.2478/amns-2024-3430
Ringeval FSchuller BBailly GAzzakhnini SFournier H(2024)EVAC 2024 – Empathic Virtual Agent Challenge: Appraisal-based Recognition of Affective StatesProceedings of the 26th International Conference on Multimodal Interaction10.1145/3678957.3689029(677-683)Online publication date: 4-Nov-2024
https://dl.acm.org/doi/10.1145/3678957.3689029
Tian XNunes BLiu YManrique R(2024)Predicting Student Engagement Using Sequential Ensemble ModelIEEE Transactions on Learning Technologies10.1109/TLT.2023.334286017(939-950)Online publication date: 2024
https://doi.org/10.1109/TLT.2023.3342860
Show More Cited By

Index Terms

EmotiW 2018: Audio-Video, Student Engagement and Group-Level Affect Prediction
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision

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Information

Published In

cover image ACM Other conferences

ICMI '18: Proceedings of the 20th ACM International Conference on Multimodal Interaction

October 2018

687 pages

ISBN:9781450356923

DOI:10.1145/3242969

General Chairs:
Sidney K. D'Mello
University of Illinois, USA
,
Panayiotis (Panos) Georgiou
University of Southern California, USA
,
Stefan Scherer
University of Southern California, USA
,
Program Chairs:
Emily Mower Provost
University of Michigan, USA
,
Mohammad Soleymani
University of Southern California, USA
,
Marcelo Worsley
Northwestern University, USA

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGCHI: Specialist Interest Group in Computer-Human Interaction of the ACM

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 October 2018

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Nvidia

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ICMI '18

Sponsor:

SIGCHI

ICMI '18: INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION

October 16 - 20, 2018

CO, Boulder, USA

Acceptance Rates

ICMI '18 Paper Acceptance Rate 63 of 149 submissions, 42%;

Overall Acceptance Rate 453 of 1,080 submissions, 42%

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Cited By

Tao HLiu CLiu Y(2024)A study on automatic identification of students’ emotional states using convolutional neural networksApplied Mathematics and Nonlinear Sciences10.2478/amns-2024-34309:1Online publication date: 25-Nov-2024
https://doi.org/10.2478/amns-2024-3430
Ringeval FSchuller BBailly GAzzakhnini SFournier H(2024)EVAC 2024 – Empathic Virtual Agent Challenge: Appraisal-based Recognition of Affective StatesProceedings of the 26th International Conference on Multimodal Interaction10.1145/3678957.3689029(677-683)Online publication date: 4-Nov-2024
https://dl.acm.org/doi/10.1145/3678957.3689029
Tian XNunes BLiu YManrique R(2024)Predicting Student Engagement Using Sequential Ensemble ModelIEEE Transactions on Learning Technologies10.1109/TLT.2023.334286017(939-950)Online publication date: 2024
https://doi.org/10.1109/TLT.2023.3342860
Chen ZSong YXu THuang ZWu XSebe N(2024)Adaptive Log-Euclidean Metrics for SPD Matrix LearningIEEE Transactions on Image Processing10.1109/TIP.2024.345193033(5194-5205)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TIP.2024.3451930
Wang XZhang DLee D(2024)Implementing the Affective Mechanism for Group Emotion Recognition With a New Graph Convolutional Network ArchitectureIEEE Transactions on Affective Computing10.1109/TAFFC.2023.332010115:3(1104-1115)Online publication date: Jul-2024
https://doi.org/10.1109/TAFFC.2023.3320101
Xu JHuang X(2024)Group-Level Emotion Recognition Using Hierarchical Dual-Branch Cross Transformer with Semi-Supervised Learning2024 IEEE 4th International Conference on Software Engineering and Artificial Intelligence (SEAI)10.1109/SEAI62072.2024.10674336(252-256)Online publication date: 21-Jun-2024
https://doi.org/10.1109/SEAI62072.2024.10674336
Pan HLuo HJiao ZDeng J(2024)Facial Expression Recognition with an Improved VGG16 Network Based on SE Modules and Residual Connections2024 4th International Conference on Machine Learning and Intelligent Systems Engineering (MLISE)10.1109/MLISE62164.2024.10674455(85-89)Online publication date: 28-Jun-2024
https://doi.org/10.1109/MLISE62164.2024.10674455
Yin C(2024)A Unified Model for Style Classification and Emotional Response AnalysisIEEE Access10.1109/ACCESS.2024.341985112(91770-91779)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3419851
Huang ZZhu YLi HYang D(2024)Dynamic facial expression recognition based on spatial key-points optimized region feature fusion and temporal self-attentionEngineering Applications of Artificial Intelligence10.1016/j.engappai.2024.108535133(108535)Online publication date: Jul-2024
https://doi.org/10.1016/j.engappai.2024.108535
Su RHe LLuo M(2024)Leveraging part-and-sensitive attention network and transformer for learner engagement detectionAlexandria Engineering Journal10.1016/j.aej.2024.06.074107(198-204)Online publication date: Nov-2024
https://doi.org/10.1016/j.aej.2024.06.074
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