Web: http://arxiv.org/abs/2112.05907

May 6, 2022, 1:12 a.m. | Jiseob Kim, Jihoon Lee, Byoung-Tak Zhang

cs.LG updates on arXiv.org arxiv.org

Face-swapping models have been drawing attention for their compelling
generation quality, but their complex architectures and loss functions often
require careful tuning for successful training. We propose a new face-swapping
model called `Smooth-Swap', which excludes complex handcrafted designs and
allows fast and stable training. The main idea of Smooth-Swap is to build
smooth identity embedding that can provide stable gradients for identity
change. Unlike the one used in previous models trained for a purely
discriminative task, the proposed embedding is …

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