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Found 9 papers, 4 papers with code
SARGAN: Spatial Attention-based Residuals for Facial Expression Manipulation
Third, we proposed to train the complete network with a residual connection which relieves the generator of pressure to generate the input face image thereby producing the desired expression by directly feeding the input image towards the end of the generator.
US-GAN: On the importance of Ultimate Skip Connection for Facial Expression Synthesis
We demonstrate the benefit of using an ultimate skip (US) connection for facial expression synthesis using generative adversarial networks (GAN).
CALText: Contextual Attention Localization for Offline Handwritten Text
Recognition of Arabic-like scripts such as Persian and Urdu is more challenging than Latin-based scripts.
Pulmonary Disease Classification Using Globally Correlated Maximum Likelihood: an Auxiliary Attention mechanism for Convolutional Neural Networks
Two complementary generalization properties of CNNs, translation invariance and equivariance, are particularly useful in detecting manifested abnormalities associated with pulmonary disease, regardless of their spatial locations within the image.
Masked Linear Regression for Learning Local Receptive Fields for Facial Expression Synthesis
Compared to facial expression recognition, expression synthesis requires a very high-dimensional mapping.
Facial Expression Recognition
Facial Expression Recognition (FER)
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Pixel-based Facial Expression Synthesis
The quality of GAN results significantly degrades when testing images are from a slightly different distribution.
Improving Explainability of Image Classification in Scenarios with Class Overlap: Application to COVID-19 and Pneumonia
Trust in predictions made by machine learning models is increased if the model generalizes well on previously unseen samples and when inference is accompanied by cogent explanations of the reasoning behind predictions.
Hazard Detection in Supermarkets using Deep Learning on the Edge
Supermarkets need to ensure clean and safe environments for both shoppers and employees.
Machine Learning at the Network Edge: A Survey
To address this issue, efforts have been made to place additional computing devices at the edge of the network, i. e close to the IoT devices where the data is generated.
