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TexSliders: Diffusion-Based Texture Editing in CLIP Space
Generative models have enabled intuitive image creation and manipulation using natural language.
Towards Enhanced Controllability of Diffusion Models
We rely on the inductive bias of the progressive denoising process of diffusion models to encode pose/layout information in the spatial structure mask and semantic/style information in the style code.
Controlled and Conditional Text to Image Generation with Diffusion Prior
We observe that Diffusion Prior can be used in a memory and compute efficient way to constrain the generation to a specific domain without altering the larger Diffusion Decoder.
PRedItOR: Text Guided Image Editing with Diffusion Prior
We combine this with structure preserving edits on the image decoder using existing approaches such as reverse DDIM to perform text guided image editing.
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