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Found 2 papers, 1 papers with code
MagFace: A Universal Representation for Face Recognition and Quality Assessment
This paper proposes MagFace, a category of losses that learn a universal feature embedding whose magnitude can measure the quality of the given face.
Ranked #1 on
Face Verification
on IJB-C
(training dataset metric)
Pooling the Convolutional Layers in Deep ConvNets for Action Recognition
It achieves the accuracy of 93. 78\% on UCF101 which is the state-of-the-art and the accuracy of 65. 62\% on HMDB51 which is comparable to the state-of-the-art.
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