AVEC 2019 Workshop and Challenge: State-of-Mind, Detecting Depression with AI, and Cross-Cultural Affect Recognition (bibtex)
by Ringeval, Fabien, Messner, Eva-Maria, Song, Siyang, Liu, Shuo, Zhao, Ziping, Mallol-Ragolta, Adria, Ren, Zhao, Soleymani, Mohammad, Pantic, Maja, Schuller, Björn, Valstar, Michel, Cummins, Nicholas, Cowie, Roddy, Tavabi, Leili, Schmitt, Maximilian, Alisamir, Sina and Amiriparian, Shahin
Abstract:
The Audio/Visual Emotion Challenge and Workshop (AVEC 2019) 'State-of-Mind, Detecting Depression with AI, and Cross-cultural Affect Recognition' is the ninth competition event aimed at the comparison of multimedia processing and machine learning methods for automatic audiovisual health and emotion analysis, with all participants competing strictly under the same conditions. The goal of the Challenge is to provide a common benchmark test set for multimodal information processing and to bring together the health and emotion recognition communities, as well as the audiovisual processing communities, to compare the relative merits of various approaches to health and emotion recognition from real-life data. This paper presents the major novelties introduced this year, the challenge guidelines, the data used, and the performance of the baseline systems on the three proposed tasks: state-of-mind recognition, depression assessment with AI, and cross-cultural affect sensing, respectively.
Reference:
AVEC 2019 Workshop and Challenge: State-of-Mind, Detecting Depression with AI, and Cross-Cultural Affect Recognition (Ringeval, Fabien, Messner, Eva-Maria, Song, Siyang, Liu, Shuo, Zhao, Ziping, Mallol-Ragolta, Adria, Ren, Zhao, Soleymani, Mohammad, Pantic, Maja, Schuller, Björn, Valstar, Michel, Cummins, Nicholas, Cowie, Roddy, Tavabi, Leili, Schmitt, Maximilian, Alisamir, Sina and Amiriparian, Shahin), In Proceedings of the 9th International on Audio/Visual Emotion Challenge and Workshop - AVEC '19, ACM Press, 2019.
Bibtex Entry:
@inproceedings{ringeval_avec_2019,
	address = {Nice, France},
	title = {{AVEC} 2019 {Workshop} and {Challenge}: {State}-of-{Mind}, {Detecting} {Depression} with {AI}, and {Cross}-{Cultural} {Affect} {Recognition}},
	isbn = {978-1-4503-6913-8},
	shorttitle = {{AVEC} 2019 {Workshop} and {Challenge}},
	url = {http://dl.acm.org/citation.cfm?doid=3347320.3357688},
	doi = {10.1145/3347320.3357688},
	abstract = {The Audio/Visual Emotion Challenge and Workshop (AVEC 2019) 'State-of-Mind, Detecting Depression with AI, and Cross-cultural Affect Recognition' is the ninth competition event aimed at the comparison of multimedia processing and machine learning methods for automatic audiovisual health and emotion analysis, with all participants competing strictly under the same conditions. The goal of the Challenge is to provide a common benchmark test set for multimodal information processing and to bring together the health and emotion recognition communities, as well as the audiovisual processing communities, to compare the relative merits of various approaches to health and emotion recognition from real-life data. This paper presents the major novelties introduced this year, the challenge guidelines, the data used, and the performance of the baseline systems on the three proposed tasks: state-of-mind recognition, depression assessment with AI, and cross-cultural affect sensing, respectively.},
	booktitle = {Proceedings of the 9th {International} on {Audio}/{Visual} {Emotion} {Challenge} and {Workshop}  - {AVEC} '19},
	publisher = {ACM Press},
	author = {Ringeval, Fabien and Messner, Eva-Maria and Song, Siyang and Liu, Shuo and Zhao, Ziping and Mallol-Ragolta, Adria and Ren, Zhao and Soleymani, Mohammad and Pantic, Maja and Schuller, Björn and Valstar, Michel and Cummins, Nicholas and Cowie, Roddy and Tavabi, Leili and Schmitt, Maximilian and Alisamir, Sina and Amiriparian, Shahin},
	month = oct,
	year = {2019},
	keywords = {UARC, Virtual Humans},
	pages = {3--12}
}
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