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Towards Controllable Face Generation with Semantic Latent Diffusion Models
To address that, in this paper we propose a SIS framework based on a novel Latent Diffusion Model architecture for human face generation and editing that is both able to reproduce and manipulate a real reference image and generate diversity-driven results.
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