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Diffusion-driven GAN Inversion for Multi-Modal Face Image Generation
To do this, we combine the strengths of Generative Adversarial networks (GANs) and diffusion models (DMs) by employing the multi-modal features in the DM into the latent space of the pre-trained GANs.
Blending-NeRF: Text-Driven Localized Editing in Neural Radiance Fields
Text-driven localized editing of 3D objects is particularly difficult as locally mixing the original 3D object with the intended new object and style effects without distorting the object's form is not a straightforward process.
Quantitative Manipulation of Custom Attributes on 3D-Aware Image Synthesis
While 3D-based GAN techniques have been successfully applied to render photo-realistic 3D images with a variety of attributes while preserving view consistency, there has been little research on how to fine-control 3D images without limiting to a specific category of objects of their properties.
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