4.7 Article

Deep Auto-Encoders With Sequential Learning for Multimodal Dimensional Emotion Recognition

Related references

Note: Only part of the references are listed.
Article Computer Science, Artificial Intelligence

Modeling Emotion in Complex Stories: The Stanford Emotional Narratives Dataset

Desmond C. Ong et al.

Summary: The article discusses the challenges and methods in time-series emotion recognition, introducing the Stanford Emotional Narratives Dataset to test different models in complex narratives. The research shows that some models perform well in emotion recognition and have potential for practical applications.

IEEE TRANSACTIONS ON AFFECTIVE COMPUTING (2021)

Article Computer Science, Information Systems

Exploring Discriminative Representations for Image Emotion Recognition With CNNs

Wei Zhang et al.

IEEE TRANSACTIONS ON MULTIMEDIA (2020)

Article Automation & Control Systems

EmotionMeter: A Multimodal Framework for Recognizing Human Emotions

Wei-Long Zheng et al.

IEEE TRANSACTIONS ON CYBERNETICS (2019)

Article Computer Science, Information Systems

Dynamic Difficulty Awareness Training for Continuous Emotion Prediction

Zixing Zhang et al.

IEEE TRANSACTIONS ON MULTIMEDIA (2019)

Article Computer Science, Artificial Intelligence

Deep Affect Prediction in-the-Wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyond

Dimitrios Kollias et al.

INTERNATIONAL JOURNAL OF COMPUTER VISION (2019)

Article Engineering, Electrical & Electronic

Learning Affective Features With a Hybrid Deep Model for Audio-Visual Emotion Recognition

Shiqing Zhang et al.

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY (2018)

Proceedings Paper Computer Science, Cybernetics

Multimodal Local-Global Ranking Fusion for Emotion Recognition

Paul Pu Liang et al.

ICMI'18: PROCEEDINGS OF THE 20TH ACM INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION (2018)

Article Engineering, Electrical & Electronic

End-to-End Multimodal Emotion Recognition Using Deep Neural Networks

Panagiotis Tzirakis et al.

IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING (2017)

Article Computer Science, Information Systems

Multimodal 2D+3D Facial Expression Recognition With Deep Fusion Convolutional Neural Network

Huibin Li et al.

IEEE TRANSACTIONS ON MULTIMEDIA (2017)

Proceedings Paper Computer Science, Artificial Intelligence

Aff-Wild: Valence and Arousal 'in-the-wild' Challenge

Stefanos Zafeiriou et al.

2017 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW) (2017)

Proceedings Paper Computer Science, Artificial Intelligence

Recognition of Affect in the wild using Deep Neural Networks

Dimitrios Kollias et al.

2017 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW) (2017)

Proceedings Paper Computer Science, Artificial Intelligence

Attention-Based Multimodal Fusion for Video Description

Chiori Hori et al.

2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV) (2017)

Article Computer Science, Artificial Intelligence

Developing crossmodal expression recognition based on a deep neural model

Pablo Barros et al.

ADAPTIVE BEHAVIOR (2016)

Proceedings Paper Acoustics

Facing Realism in Spontaneous Emotion Recognition from Speech: Feature Enhancement by Autoencoder with LSTM Neural Networks

Zixing Zhang et al.

17TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2016), VOLS 1-5: UNDERSTANDING SPEECH PROCESSING IN HUMANS AND MACHINES (2016)

Article Computer Science, Artificial Intelligence

ImageNet Large Scale Visual Recognition Challenge

Olga Russakovsky et al.

INTERNATIONAL JOURNAL OF COMPUTER VISION (2015)

Proceedings Paper Computer Science, Artificial Intelligence

Learning Spatiotemporal Features with 3D Convolutional Networks

Du Tran et al.

2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV) (2015)

Article Computer Science, Artificial Intelligence

LSTM-Modeling of continuous emotions in an audiovisual affect recognition framework

Martin Woellmer et al.

IMAGE AND VISION COMPUTING (2013)