论文标题
时间一致的语义视频编辑
Temporally Consistent Semantic Video Editing
论文作者
论文摘要
生成的对抗网络（GAN）表现出了真实图像的令人印象深刻的图像生成质量和语义编辑功能，例如更改对象类，修改属性或传输样式。但是，将这些基于GAN的编辑应用于每个帧不可避免地会导致暂时闪烁的工件。我们提出了一种简单而有效的方法，以促进时间连贯的视频编辑。我们的核心思想是通过优化潜在代码和预训练的发电机来最大程度地减少时间光度不一致。我们评估了在不同领域和GAN倒置技术上编辑的质量，并对基线显示出优惠的结果。
Generative adversarial networks (GANs) have demonstrated impressive image generation quality and semantic editing capability of real images, e.g., changing object classes, modifying attributes, or transferring styles. However, applying these GAN-based editing to a video independently for each frame inevitably results in temporal flickering artifacts. We present a simple yet effective method to facilitate temporally coherent video editing. Our core idea is to minimize the temporal photometric inconsistency by optimizing both the latent code and the pre-trained generator. We evaluate the quality of our editing on different domains and GAN inversion techniques and show favorable results against the baselines.
