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HoloNet: towards robust emotion recognition in the wild

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References

2008A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions2,797 cited
2013Combining modality specific deep neural networks for emotion recognition in video391 cited
2011Emotion recognition using a hierarchical binary decision tree approach355 cited
2015Video and Image based Emotion Recognition Challenges in the Wild305 cited
2015A mixed bag of emotions: Model, predict, and transfer emotion distributions258 cited
2014Emotion Recognition In The Wild Challenge 2014216 cited
2014Combining Multiple Kernel Methods on Riemannian Manifold for Emotion Recognition in the Wild202 cited
2013Emotion recognition in the wild challenge 2013179 cited
2016EmotiW 2016: video and group-level emotion recognition challenges147 cited

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2018A visual attention based ROI detection method for facial expression recognition107 cited
2018Multi-cue fusion for emotion recognition in the wild98 cited
2017Audio-visual emotion recognition using deep transfer learning and multiple temporal models

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2021Facial Expression Recognition: A Review of Trends and Techniques81 cited

2022Clip-aware expressive feature learning for video-based facial expression recognition81 cited

2017Deeper cascaded peak-piloted network for weak expression recognition80 cited

2019Exploring Emotion Features and Fusion Strategies for Audio-Video Emotion Recognition77 cited

2019Facial Expression Recognition Using a Temporal Ensemble of Multi-Level Convolutional Neural Networks72 cited

2019Two-level attention with two-stage multi-task learning for facial emotion recognition71 cited

2018Hand-Crafted Feature Guided Deep Learning for Facial Expression Recognition65 cited

2018Leveraging Large Face Recognition Data for Emotion Classification61 cited

2021Deep neural network-based fusion model for emotion recognition using visual data50 cited

2017Convolutional neural networks pretrained on large face recognition datasets for emotion classification from video49 cited

2017Multi-modal emotion recognition using semi-supervised learning and multiple neural networks in the wild47 cited