Residual Parameter Transfer for Deep Domain Adaptation

CVPR 2018 Artem RozantsevMathieu SalzmannPascal Fua

The goal of Deep Domain Adaptation is to make it possible to use Deep Nets trained in one domain where there is enough annotated training data in another where there is little or none. Most current approaches have focused on learning feature representations that are invariant to the changes that occur when going from one domain to the other, which means using the same network parameters in both domains... (read more)

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