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Summary for AVEC 2017: Real-life Depression and Affect Challenge and Workshop

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Maja PanticAuthors Info & Claims

MM '17: Proceedings of the 25th ACM international conference on Multimedia

Pages 1963 - 1964

https://doi.org/10.1145/3123266.3132049

Published: 23 October 2017 Publication History

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Abstract

The seventh Audio-Visual Emotion Challenge and workshop AVEC 2017 was held in conjunction with ACM Multimedia'17. This year, the AVEC series addresses two distinct sub-challenges: emotion recognition and depression detection. The Affect Sub-Challenge is based on a novel dataset of human-human interactions recorded 'in-the-wild', whereas the Depression Sub-Challenge is based on the same dataset as the one used in AVEC 2016, with human-agent interactions. In this summary, we mainly describe participation and its conditions.

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Ishimaru MOkada YUchiyama RHoriguchi RToyoshima I(2023)Classification of Depression and Its Severity Based on Multiple Audio Features Using a Graphical Convolutional Neural NetworkInternational Journal of Environmental Research and Public Health10.3390/ijerph2002158820:2(1588)Online publication date: 15-Jan-2023
https://doi.org/10.3390/ijerph20021588
Schuller BLochner JQian KHu B(2022)COVID-19’s Impact on Mental Health—The Hour of Computational Aid?IEEE Transactions on Computational Social Systems10.1109/TCSS.2022.31918219:4(967-973)Online publication date: Aug-2022
https://doi.org/10.1109/TCSS.2022.3191821
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Index Terms

Summary for AVEC 2017: Real-life Depression and Affect Challenge and Workshop
1. General and reference
  1. Cross-computing tools and techniques
    1. Performance
2. Security and privacy
  1. Security services
    1. Authentication
      1. Biometrics

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Information & Contributors

Information

Published In

MM '17: Proceedings of the 25th ACM international conference on Multimedia

October 2017

2028 pages

ISBN:9781450349062

DOI:10.1145/3123266

General Chairs:
Qiong Liu
FXPAL, USA
,
Rainer Lienhart
Universität Augsburg, Germany
,
Haohong Wang
TCL America, USA
,
Program Chairs:
Sheng-Wei "Kuan-Ta" Chen
Academia Sinica, Taiwan
,
Susanne Boll
University of Oldenburg, Germany
,
Phoebe Chen
La Trobe University, Australia
,
Gerald Friedland
Lawrence Livermore National Lab, USA
,
Jia Li
Google, USA
,
Shuicheng Yan
Qihoo 360, China

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 October 2017

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Conference

MM '17

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SIGMM

MM '17: ACM Multimedia Conference

October 23 - 27, 2017

California, Mountain View, USA

Acceptance Rates

MM '17 Paper Acceptance Rate 189 of 684 submissions, 28%;

Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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Cited By

View all

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https://doi.org/10.3390/s24144721
Ishimaru MOkada YUchiyama RHoriguchi RToyoshima I(2023)Classification of Depression and Its Severity Based on Multiple Audio Features Using a Graphical Convolutional Neural NetworkInternational Journal of Environmental Research and Public Health10.3390/ijerph2002158820:2(1588)Online publication date: 15-Jan-2023
https://doi.org/10.3390/ijerph20021588
Schuller BLochner JQian KHu B(2022)COVID-19’s Impact on Mental Health—The Hour of Computational Aid?IEEE Transactions on Computational Social Systems10.1109/TCSS.2022.31918219:4(967-973)Online publication date: Aug-2022
https://doi.org/10.1109/TCSS.2022.3191821
Khorram SMcInnis MProvost E(2021)Jointly Aligning and Predicting Continuous Emotion AnnotationsIEEE Transactions on Affective Computing10.1109/TAFFC.2019.291704712:4(1069-1083)Online publication date: 1-Oct-2021
https://doi.org/10.1109/TAFFC.2019.2917047
Elfaki AAsnawi AJusoh AIsmail AIbrahim SMohamed Azmin NWahidah Binti Nik Hashim N(2021)Using the Short-Time Fourier Transform and ResNet to Diagnose Depression from Speech Data2021 IEEE International Conference on Computing (ICOCO)10.1109/ICOCO53166.2021.9673562(372-376)Online publication date: 17-Nov-2021
https://doi.org/10.1109/ICOCO53166.2021.9673562
Tse KHung K(2020)User Behavioral Biometrics Identification on Mobile Platform using Multimodal Fusion of Keystroke and Swipe Dynamics and Recurrent Neural Network2020 IEEE 10th Symposium on Computer Applications & Industrial Electronics (ISCAIE)10.1109/ISCAIE47305.2020.9108839(262-267)Online publication date: Apr-2020
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Vielzeuf VLechervy APateux SJurie F(2019)Multilevel Sensor Fusion With Deep LearningIEEE Sensors Letters10.1109/LSENS.2018.28789083:1(1-4)Online publication date: Jan-2019
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Tang YMao QJia HSong HZhan Y(2019)An Emotion-Embedded Visual Attention Model for Dimensional Emotion Context LearningIEEE Access10.1109/ACCESS.2019.29117147(72457-72468)Online publication date: 2019
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Vielzeuf VLechervy APateux SJurie F(2019)CentralNet: A Multilayer Approach for Multimodal FusionComputer Vision – ECCV 2018 Workshops10.1007/978-3-030-11024-6_44(575-589)Online publication date: 23-Jan-2019
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Ringeval FSchuller BValstar MCowie RKaya HSchmitt MAmiriparian SCummins NLalanne DMichaud ACiftçi EGüleç HSalah APantic MRingeval FSchuller BValstar MCowie RPantic M(2018)AVEC 2018 Workshop and ChallengeProceedings of the 2018 on Audio/Visual Emotion Challenge and Workshop10.1145/3266302.3266316(3-13)Online publication date: 15-Oct-2018
https://dl.acm.org/doi/10.1145/3266302.3266316

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AVEC 2017: Real-life Depression, and Affect Recognition Workshop and Challenge

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