Learning face and upper-body emotion recognition - Henrique Siqueira
This work has received funding from the European Union under the SOCRATES project (No. 721619). My GitHub: https://github.com/siqueira-hc The Facial Expression Recognition Framework: https://github.com/siqueira-hc/Efficient-Facial-Feature-Learning-with-Wide-Ensemble-based-Convolutional-Neural-Networks Knowledge Technology's GitHub: https://github.com/knowledgetechnologyuhh/ Knowledge Technology's website: https://www.inf.uni-hamburg.de/en/inst/ab/wtm/ List of publications under the SOCRATES project: Siqueira, H., Magg, S. and Wermter, S. (2020). Efficient Facial Feature Learning with Wide Ensemble-based Convolutional Neural Networks. Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), pages 1–1, New York, USA. Link: https://www2.informatik.uni-hamburg.de/wtm/publications/2020/SMW20/SMW20.pdf Lindt, A., Barros, P., Siqueira, H. and Wermter, S. (2019). Facial Expression Editing with Continuous Emotion Labels. Proceedings of the International Conference on Automatic Face Gesture Recognition (FG), pages 1–8, Lille, France. Link: https://ieeexplore.ieee.org/document/8756558 Barros, P., Churamani, N., Lakomkin, E., Siqueira, H., Sutherland, A. and Wermter, S. (2018). The OMG-Emotion Behavior Dataset. Proceedings of the International Joint Conference on Neural Networks (IJCNN), pages 1–7, Rio de Janeiro, Brazil. Link: https://ieeexplore.ieee.org/document/8489099 Siqueira, H. (2018) An Adaptive Neural Approach Based on Ensemble and Multitask Learning for Affect Recognition. Proceedings of the International Ph.D. Conference on Safe and Social Robotics (SSR), pages 49–52, Madrid, Spain. Link: https://www2.informatik.uni-hamburg.de/wtm/publications/2018/Siq18/index.php?compact=true Siqueira, H., Barros, P., Magg, S., Weber, C. and Wermter, S. (2018). A Sub-Layered Hierarchical Pyramidal Neural Architecture for Facial Expression Recognition. Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), pages 1–6, Bruges, Belgium. Link: https://www.elen.ucl.ac.be/Proceedings/esann/esannpdf/es2018-166.pdf Siqueira, H., Barros, P., Magg, S. and Wermter, S. (2018). An Ensemble with Shared Representations Based on Convolutional Networks for Continually Learning Facial Expressions. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 1563–1568, Madrid, Spain. Link: https://ieeexplore.ieee.org/abstract/document/8594276 Siqueira, H., Sutherland, A., Barros, P., Kerzel, M., Magg, S. and Wermter, S. (2018). Disambiguating Affective Stimulus Associations for Robot Perception and Dialogue. Proceedings of the IEEE-RAS International Conference on Humanoid Robots (Humanoids), pages 433–440, Beijing, China. Link: https://www2.informatik.uni-hamburg.de/wtm/publications/2018/SSBKMW18/index.php?compact=true
This work has received funding from the European Union under the SOCRATES project (No. 721619). My GitHub: https://github.com/siqueira-hc The Facial Expression Recognition Framework: https://github.com/siqueira-hc/Efficient-Facial-Feature-Learning-with-Wide-Ensemble-based-Convolutional-Neural-Networks Knowledge Technology's GitHub: https://github.com/knowledgetechnologyuhh/ Knowledge Technology's website: https://www.inf.uni-hamburg.de/en/inst/ab/wtm/ List of publications under the SOCRATES project: Siqueira, H., Magg, S. and Wermter, S. (2020). Efficient Facial Feature Learning with Wide Ensemble-based Convolutional Neural Networks. Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), pages 1–1, New York, USA. Link: https://www2.informatik.uni-hamburg.de/wtm/publications/2020/SMW20/SMW20.pdf Lindt, A., Barros, P., Siqueira, H. and Wermter, S. (2019). Facial Expression Editing with Continuous Emotion Labels. Proceedings of the International Conference on Automatic Face Gesture Recognition (FG), pages 1–8, Lille, France. Link: https://ieeexplore.ieee.org/document/8756558 Barros, P., Churamani, N., Lakomkin, E., Siqueira, H., Sutherland, A. and Wermter, S. (2018). The OMG-Emotion Behavior Dataset. Proceedings of the International Joint Conference on Neural Networks (IJCNN), pages 1–7, Rio de Janeiro, Brazil. Link: https://ieeexplore.ieee.org/document/8489099 Siqueira, H. (2018) An Adaptive Neural Approach Based on Ensemble and Multitask Learning for Affect Recognition. Proceedings of the International Ph.D. Conference on Safe and Social Robotics (SSR), pages 49–52, Madrid, Spain. Link: https://www2.informatik.uni-hamburg.de/wtm/publications/2018/Siq18/index.php?compact=true Siqueira, H., Barros, P., Magg, S., Weber, C. and Wermter, S. (2018). A Sub-Layered Hierarchical Pyramidal Neural Architecture for Facial Expression Recognition. Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), pages 1–6, Bruges, Belgium. Link: https://www.elen.ucl.ac.be/Proceedings/esann/esannpdf/es2018-166.pdf Siqueira, H., Barros, P., Magg, S. and Wermter, S. (2018). An Ensemble with Shared Representations Based on Convolutional Networks for Continually Learning Facial Expressions. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 1563–1568, Madrid, Spain. Link: https://ieeexplore.ieee.org/abstract/document/8594276 Siqueira, H., Sutherland, A., Barros, P., Kerzel, M., Magg, S. and Wermter, S. (2018). Disambiguating Affective Stimulus Associations for Robot Perception and Dialogue. Proceedings of the IEEE-RAS International Conference on Humanoid Robots (Humanoids), pages 433–440, Beijing, China. Link: https://www2.informatik.uni-hamburg.de/wtm/publications/2018/SSBKMW18/index.php?compact=true