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Found 5 papers, 3 papers with code
Representative Forgery Mining for Fake Face Detection
Although vanilla Convolutional Neural Network (CNN) based detectors can achieve satisfactory performance on fake face detection, we observe that the detectors tend to seek forgeries on a limited region of face, which reveals that the detectors is short of understanding of forgery.
Learn From All: Erasing Attention Consistency for Noisy Label Facial Expression Recognition
We find that FER models remember noisy samples by focusing on a part of the features that can be considered related to the noisy labels instead of learning from the whole features that lead to the latent truth.
Facial Expression Recognition
Facial Expression Recognition (FER)
+1
Relative Uncertainty Learning for Facial Expression Recognition
To quantify these uncertainties and achieve good performance under noisy data, we regard uncertainty as a relative concept and propose an innovative uncertainty learning method called Relative Uncertainty Learning (RUL).
Ranked #10 on
Facial Expression Recognition (FER)
on RAF-DB
Facial Expression Recognition
Facial Expression Recognition (FER)
MLFW: A Database for Face Recognition on Masked Faces
As more and more people begin to wear masks due to current COVID-19 pandemic, existing face recognition systems may encounter severe performance degradation when recognizing masked faces.
Ranked #1 on
Face Recognition
on MLFW
RHanDS: Refining Malformed Hands for Generated Images with Decoupled Structure and Style Guidance
The style guidance is a hand image, e. g., the malformed hand itself, and is employed to furnish the style reference for hand refining.
