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Facial Expression Recognition using the Bilinear Pooling

https://doi.org/10.5220/0008928002940301
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-030-01231-1_10openalex-snapshot
Image Reassembly Combining Deep Learning and Shortest Path Problem
inferredcites →https://doi.org/10.1007/978-3-319-16817-3_10openalex-snapshot
Deeply Learning Deformable Facial Action Parts Model for Dynamic Expression Analysis
inferredcites →https://doi.org/10.1007/978-3-642-33783-3_58openalex-snapshot
Disentangling Factors of Variation for Facial Expression Recognition
inferredcites →https://doi.org/10.1016/j.imavis.2009.11.005openalex-snapshot
A new ranking method for principal components analysis and its application to face image analysis
inferredcites →https://doi.org/10.1016/j.imavis.2011.07.002openalex-snapshot
Facial expression recognition from near-infrared videos
inferredcites →https://doi.org/10.1016/j.neucom.2020.01.067openalex-snapshot
Fine-grained facial expression analysis using dimensional emotion model
inferredcites →https://doi.org/10.1109/cvpr.2013.439openalex-snapshot
Capturing Complex Spatio-temporal Relations among Facial Muscles for Facial Expression Recognition
inferredcites →https://doi.org/10.1109/cvpr.2014.233openalex-snapshot
Facial Expression Recognition via a Boosted Deep Belief Network
inferredcites →https://doi.org/10.1109/cvpr.2016.38openalex-snapshot
TI-POOLING: Transformation-Invariant Pooling for Feature Learning in Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/cvpr.2017.195openalex-snapshot
Xception: Deep Learning with Depthwise Separable Convolutions
inferredcites →https://doi.org/10.1109/cvprw.2010.5543262openalex-snapshot
The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression
inferredcites →https://doi.org/10.1109/cvprw.2017.282openalex-snapshot
Facial Expression Recognition Using Enhanced Deep 3D Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/iccvw.2011.6130446openalex-snapshot
Facial expression recognition with temporal modeling of shapes
inferredcites →https://doi.org/10.1109/iccvw.2015.12openalex-snapshot
Do Deep Neural Networks Learn Facial Action Units When Doing Expression Recognition?
inferredcites →https://doi.org/10.1109/icme.2005.1521424openalex-snapshot
Web-Based Database for Facial Expression Analysis
inferredcites →https://doi.org/10.1109/icpr.2018.8545853openalex-snapshot
Patch-Gated CNN for Occlusion-aware Facial Expression Recognition
inferredcites →https://doi.org/10.1109/ijcnn.2019.8851942openalex-snapshot
Deep Fusion: An Attention Guided Factorized Bilinear Pooling for Audio-video Emotion Recognition
inferredcites →https://doi.org/10.1109/t-affc.2013.4openalex-snapshot
DISFA: A Spontaneous Facial Action Intensity Database
inferredcites →https://doi.org/10.1109/tmm.2018.2844085openalex-snapshot
Facial Expression Recognition Using Hierarchical Features With Deep Comprehensive Multipatches Aggregation Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/tpami.2017.2723400openalex-snapshot
Bilinear Convolutional Neural Networks for Fine-Grained Visual Recognition
inferredcites →https://doi.org/10.3390/app7111184openalex-snapshot
NIRExpNet: Three-Stream 3D Convolutional Neural Network for Near Infrared Facial Expression Recognition
inferredcites →https://doi.org/10.48550/arxiv.1704.06756openalex-snapshot
Convolutional Neural Networks for Facial Expression Recognition

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4189323openalex-extracted
inferred← citeshttps://doi.org/10.1007/s11548-020-02283-zopenalex-snapshot
A bilinear convolutional neural network for lung nodules classification on CT images
inferred← citeshttps://doi.org/10.1007/s41870-022-01093-7openalex-snapshot
Effective recognition of facial emotions using dual transfer learned feature vectors and support vector machine
inferred← citeshttps://doi.org/10.1016/j.inffus.2022.10.002openalex-snapshot
EmoMV: Affective music-video correspondence learning datasets for classification and retrieval
inferred← citeshttps://doi.org/10.1109/atsip55956.2022.9805902openalex-snapshot
Deepfake video detection using InceptionResnetV2
inferred← citeshttps://doi.org/10.1145/3430199.3430211openalex-snapshot
Transfer Learning Vs. Fine-Tuning in Bilinear CNN for Lung Nodules Classification on CT Scans
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