Efficient Spatial Temporal Convolutional Features for Audiovisual Continuous Affect Recognition-Reference-Cited by-同舟云学术

Efficient Spatial Temporal Convolutional Features for Audiovisual Continuous Affect Recognition

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 9th International on Audio/Visual Emotion Challenge and Workshop - AVEC '19
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Author:

Chen Haifeng¹,Deng Yifan¹,Cheng Shiwen¹,Wang Yixuan¹,Jiang Dongmei²,Sahli Hichem³

Affiliation:

1. Northwestern Polytechnical University, Xi'an, China

2. Northwestern Polytechnical University & PengCheng Laboratory, Xi'an, China

3. Vrije University Brussel & Interuniversity Microelectronics Centre, Brussels, Belgium

Publisher

ACM Press

Reference32 articles.

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4. Yusuf Aytar, Carl Vondrick, and Antonio Torralba. 2016. Soundnet: Learning sound representations from unlabeled video. In Advances in Neural Information Processing Systems.

5. Shaojie Bai, J. Zico Kolter, and Vladlen Koltun. 2018. An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling. CoRR, Vol. abs/1803.01271 (2018). arxiv: 1803.01271 http://arxiv.org/abs/1803.01271

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