  Talking face generation with great practical significance has attracted more
attention in recent audio-visual studies. How to achieve accurate lip
synchronization is a long-standing challenge to be further investigated.
Motivated by xxx, in this paper, an AttnWav2Lip model is proposed by
incorporating spatial attention module and channel attention module into
lip-syncing strategy. Rather than focusing on the unimportant regions of the
face image, the proposed AttnWav2Lip model is able to pay more attention on the
lip region reconstruction. To our limited knowledge, this is the first attempt
to introduce attention mechanism to the scheme of talking face generation. An
extensive experiments have been conducted to evaluate the effectiveness of the
proposed model. Compared to the baseline measured by LSE-D and LSE-C metrics, a
superior performance has been demonstrated on the benchmark lip synthesis
datasets, including LRW, LRS2 and LRS3.
