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Our work focuses on GAN-based, temporally consistent video editing.
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author
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2026-03-05 08:04:40
raw text
Temporally Consistent Semantic Video Editing Temporally Consistent Semantic Video Editing ECCV 2022 Yiran Xu 1 , Badour AlBahar 2 , Jia-Bin Huang 1 , 1 University of Maryland, College Park, 2 Virginia Tech arXiv Code Abstract 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 r...
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