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Found 5 papers, 1 papers with code
E4S: Fine-grained Face Swapping via Editing With Regional GAN Inversion
Based on this disentanglement, face swapping can be simplified as style and mask swapping.
TextIR: A Simple Framework for Text-based Editable Image Restoration
We use the text-image feature compatibility of the CLIP to alleviate the difficulty of fusing text and image features.
Fine-Grained Face Swapping via Regional GAN Inversion
We rethink face swapping from the perspective of fine-grained face editing, \textit{i. e., ``editing for swapping'' (E4S)}, and propose a framework that is based on the explicit disentanglement of the shape and texture of facial components.
PS-NeRV: Patch-wise Stylized Neural Representations for Videos
We study how to represent a video with implicit neural representations (INRs).
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Video Reconstruction
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Improving the Latent Space of Image Style Transfer
The content contrastive loss enables the encoder to retain more available details.
