arXiv:1712.03451
공식 코드 · Papers with Code
CycleGAN Face-off
원문 초록
Face-off is an interesting case of style transfer where the facial expressions and attributes of one person could be fully transformed to another face. We are interested in the unsupervised training process which only requires two sequences of unaligned video frames from each person and learns what shared attributes to extract automatically. In this project, we explored various improvements for adversarial training (i.e. CycleGAN[Zhu et al., 2017]) to capture details in facial expressions and head poses and thus generate transformation videos of higher consistency and stability.
함께 살펴볼 논문
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SA-LUT: Spatial Adaptive 4D Look-Up Table for Photorealistic Style Transfer
Implicit Inversion turns CLIP into a Decoder
Pseudo Multi-Source Domain Generalization: Bridging the Gap Between Single and Multi-Source Domain Generalization
CLIPGaussian: Universal and Multimodal Style Transfer Based on Gaussian Splatting
Graph Style Transfer for Counterfactual Explainability
Style Transfer with Diffusion Models for Synthetic-to-Real Domain Adaptation
토론
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