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Found 15 papers, 6 papers with code
ObjectDrop: Bootstrapping Counterfactuals for Photorealistic Object Removal and Insertion
To tackle this challenge, we propose bootstrap supervision; leveraging our object removal model trained on a small counterfactual dataset, we synthetically expand this dataset considerably.
PALP: Prompt Aligned Personalization of Text-to-Image Models
We term our approach prompt-aligned personalization.
RealFill: Reference-Driven Generation for Authentic Image Completion
Once personalized, RealFill is able to complete a target image with visually compelling contents that are faithful to the original scene.
Computational Long Exposure Mobile Photography
Background blur images, also called panning photography, are captured while the camera is tracking a moving subject, to produce an image of a sharp subject over a background blurred by relative motion.
HyperDreamBooth: HyperNetworks for Fast Personalization of Text-to-Image Models
By composing these weights into the diffusion model, coupled with fast finetuning, HyperDreamBooth can generate a person's face in various contexts and styles, with high subject details while also preserving the model's crucial knowledge of diverse styles and semantic modifications.
Dreamix: Video Diffusion Models are General Video Editors
Our approach uses a video diffusion model to combine, at inference time, the low-resolution spatio-temporal information from the original video with new, high resolution information that it synthesized to align with the guiding text prompt.
Null-text Inversion for Editing Real Images using Guided Diffusion Models
Our Null-text inversion, based on the publicly available Stable Diffusion model, is extensively evaluated on a variety of images and prompt editing, showing high-fidelity editing of real images.
Ranked #4 on
Text-based Image Editing
on PIE-Bench
DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation
Once the subject is embedded in the output domain of the model, the unique identifier can be used to synthesize novel photorealistic images of the subject contextualized in different scenes.
Prompt-to-Prompt Image Editing with Cross Attention Control
Editing is challenging for these generative models, since an innate property of an editing technique is to preserve most of the original image, while in the text-based models, even a small modification of the text prompt often leads to a completely different outcome.
Ranked #14 on
Text-based Image Editing
on PIE-Bench
MyStyle: A Personalized Generative Prior
Given a small reference set of portrait images of a person (~100), we tune the weights of a pretrained StyleGAN face generator to form a local, low-dimensional, personalized manifold in the latent space.
Deep Saliency Prior for Reducing Visual Distraction
Using only a model that was trained to predict where people look at images, and no additional training data, we can produce a range of powerful editing effects for reducing distraction in images.
Sky Optimization: Semantically aware image processing of skies in low-light photography
The sky is a major component of the appearance of a photograph, and its color and tone can strongly influence the mood of a picture.
Handheld Mobile Photography in Very Low Light
Aside from the physical limits imposed by read noise and photon shot noise, these cameras are typically handheld, have small apertures and sensors, use mass-produced analog electronics that cannot easily be cooled, and are commonly used to photograph subjects that move, like children and pets.
Synthetic Depth-of-Field with a Single-Camera Mobile Phone
Shallow depth-of-field is commonly used by photographers to isolate a subject from a distracting background.
Megastereo: Constructing High-Resolution Stereo Panoramas
As our first contribution, we describe the necessary correction steps and a compact representation for the input images in order to achieve a highly accurate approximation to the required ray space.
