字节开源嘴型同步模型LatentSync，实现超真实口型同步
近日，字节跳动发布了名为 LatentSync 的新型口型同步框架，旨在利用音频条件潜在扩散模型实现更精确的口型同步。该框架基于Stable Diffusion，针对时间一致性做了优化。与以往的基于像素空间扩散或两阶段生成的方法不同，LatentSync 采用端到端的方式，无需中间运动表示，能够直接建模复杂的音频与视觉之间的关系。在 LatentSync 的框架中，首先使用 Whisper 将音频频谱图转换为音频嵌入，并通过交叉注意力层将其集成到 U-Net 模型中。框架通过将参考帧和掩码帧与噪声潜在变量进行通道级拼接
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