M3D-GAN introduces modality subnets, a shared computing body, and a universal attention module to enable translation across text, image, and speech modalities and their internal domains.
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cs.CV 2years
2019 2verdicts
UNVERDICTED 2representative citing papers
Random pixel permutation destroys local correlations in images, causing standard CNN classification accuracy to drop depending on class similarities while dilated convolutions recover some performance.
citing papers explorer
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M3D-GAN: Multi-Modal Multi-Domain Translation with Universal Attention
M3D-GAN introduces modality subnets, a shared computing body, and a universal attention module to enable translation across text, image, and speech modalities and their internal domains.
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Convolutional Neural Networks on Randomized Data
Random pixel permutation destroys local correlations in images, causing standard CNN classification accuracy to drop depending on class similarities while dilated convolutions recover some performance.