Paper

EFANet: Exchangeable Feature Alignment Network for Arbitrary Style Transfer

Style transfer has been an important topic both in computer vision and graphics. Since the seminal work of Gatys et al. first demonstrates the power of stylization through optimization in the deep feature space, quite a few approaches have achieved real-time arbitrary style transfer with straightforward statistic matching techniques... (read more)

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