Reliable crowdsourcing and deep localitypreserving learning for expression recognition in the wild, CVPR, pp.2584-2593, 2017. ,
Emotion distribution recognition from facial expressions, ACMMM, 2015. ,
Expression recognition for severely demented patients in music reminiscence-therapy, 2017. ,
URL : https://hal.archives-ouvertes.fr/hal-01543231
Joint fine-tuning in deep neural networks for facial expression recognition, ICCV, pp.2983-2991, 2015. ,
Peak-piloted deep network for facial expression recognition, ECCV, pp.425-442, 2016. ,
Facenet2expnet: Regularizing a deep face recognition net for expression recognition, Int. Conf. on Automatic Face & Gesture Recognition (FG), pp.118-126, 2017. ,
Identity-aware convolutional neural network for facial expression recognition, Int. Conf. on Automatic Face & Gesture Recognition (FG), pp.558-565, 2017. ,
Deep learning for emotion recognition on small datasets using transfer learning, ACM Int. Conf. on multimodal interaction, pp.443-449, 2015. ,
A weakly supervised learning technique for classifying facial expressions, Pattern Recognition Letters, vol.128, pp.162-168, 2019. ,
URL : https://hal.archives-ouvertes.fr/hal-02381439
Enhanced semi-supervised learning for multimodal emotion recognition, ICASSP, pp.5185-5189, 2016. ,
Semi-supervised self-training of object detection models, WACV Workshops, 2005. ,
Rethinking the inception architecture for computer vision, CVPR, pp.2818-2826, 2016. ,
Data dropout: Optimizing training data for convolutional neural networks, Int. Conf. on Tools with Artificial Intelligence (ICTAI), pp.39-46, 2018. ,
Instance-based deep transfer learning, pp.367-375, 2019. ,
Mentornet: Learning data-driven curriculum for very deep neural networks on corrupted labels, in ICML, pp.2309-2318, 2018. ,
Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks, Workshop on Challenges in Representation Learning, ICML, vol.3, p.2, 2013. ,
Facial expression recognition via a boosted deep belief network, CVPR, pp.1805-1812, 2014. ,
Facial expression recognition with convolutional neural networks: coping with few data and the training sample order, Pattern Recog. (PR), vol.61, pp.610-628, 2017. ,
Facial expression recognition with inconsistently annotated datasets, in ECCV, pp.222-259, 2018. ,
Learning and transferring mid-level image representations using convolutional neural networks, CVPR, pp.1717-1724, 2014. ,
URL : https://hal.archives-ouvertes.fr/hal-00911179
Deep face recognition, BMVC, vol.1, p.6, 2015. ,
Learning feature representations with kmeans, Neural networks: Tricks of the trade, pp.561-580, 2012. ,
Semi-supervised learning with ladder networks, NIPS, pp.3546-3554, 2015. ,
Unsupervised representation learning with deep convolutional generative adversarial networks, 2016. ,
Learning from noisy large-scale datasets with minimal supervision, pp.839-847, 2017. ,
Learning from noisy labels with distillation, pp.1910-1918, 2017. ,
Understanding black-box predictions via influence functions, pp.1885-1894, 2017. ,
The extended cohn-kanade dataset (ck+): A complete dataset for action unit and emotion-specified expression, CVPR Workshops, pp.94-101, 2010. ,
Presentation and validation of the radboud faces database, Cognition and emotion, vol.24, issue.8, pp.1377-1388, 2010. ,
Affectnet: A database for facial expression, valence, and arousal computing in the wild, IEEE Trans. on Affective Comput, 2017. ,
Patch-gated cnn for occlusionaware facial expression recognition, 2018. ,
Cake: Compact and accurate k-dimensional representation of emotion, BMVC Workshop, 2018. ,
URL : https://hal.archives-ouvertes.fr/hal-01849908
Joint face detection and alignment using multitask cascaded convolutional networks, IEEE Signal Proces. Let, vol.23, issue.10, pp.1499-1503, 2016. ,
Lomo: Latent ordinal model for facial analysis in videos, CVPR, pp.5580-5589, 2016. ,
An efficient unconstrained facial expression recognition algorithm based on stack binarized auto-encoders and binarized neural networks, Neurocomputing, vol.267, pp.385-395, 2017. ,
Action unit selective feature maps in deep networks for facial expression recognition, pp.2031-2038, 2017. ,
Facial expression recognition and histograms of oriented gradients: a comprehensive study, SpringerPlus, vol.4, issue.1, p.645, 2015. ,
An occam's razor view on learning audiovisual emotion recognition with small training sets, ICMI, pp.589-593, 2018. ,
URL : https://hal.archives-ouvertes.fr/hal-01854019