text-guided-image-editing
12 papers with code • 0 benchmarks • 0 datasets
Editing images using text prompts.
Benchmarks
These leaderboards are used to track progress in text-guided-image-editing
Most implemented papers
Versatile Diffusion: Text, Images and Variations All in One Diffusion Model
shi-labs/versatile-diffusion
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ICCV 2023
In this work, we expand the existing single-flow diffusion pipeline into a multi-task multimodal network, dubbed Versatile Diffusion (VD), that handles multiple flows of text-to-image, image-to-text, and variations in one unified model.
On Distillation of Guided Diffusion Models
ermongroup/SDEdit
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CVPR 2023
For standard diffusion models trained on the pixel-space, our approach is able to generate images visually comparable to that of the original model using as few as 4 sampling steps on ImageNet 64x64 and CIFAR-10, achieving FID/IS scores comparable to that of the original model while being up to 256 times faster to sample from.
EDICT: Exact Diffusion Inversion via Coupled Transformations
salesforce/edict
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CVPR 2023
EDICT enables mathematically exact inversion of real and model-generated images by maintaining two coupled noise vectors which are used to invert each other in an alternating fashion.
MDP: A Generalized Framework for Text-Guided Image Editing by Manipulating the Diffusion Path
Image generation using diffusion can be controlled in multiple ways.
Blended Diffusion for Text-driven Editing of Natural Images
omriav/blended-diffusion
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CVPR 2022
Natural language offers a highly intuitive interface for image editing.
DE-Net: Dynamic Text-guided Image Editing Adversarial Networks
tobran/de-net
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To solve these limitations, we propose: (i) a Dynamic Editing Block (DEBlock) which composes different editing modules dynamically for various editing requirements.
Blended Latent Diffusion
omriav/blended-latent-diffusion
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Our solution leverages a recent text-to-image Latent Diffusion Model (LDM), which speeds up diffusion by operating in a lower-dimensional latent space.
SinDDM: A Single Image Denoising Diffusion Model
Here, we introduce a framework for training a DDM on a single image.
In-Context Learning Unlocked for Diffusion Models
zhendong-wang/prompt-diffusion
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To achieve this, we propose a vision-language prompt that can model a wide range of vision-language tasks and a diffusion model that takes it as input.
InstructEdit: Improving Automatic Masks for Diffusion-based Image Editing With User Instructions
In this work, we propose a framework termed InstructEdit that can do fine-grained editing based on user instructions.
