Image Inpainting

270 papers with code • 12 benchmarks • 17 datasets

Image Inpainting is a task of reconstructing missing regions in an image. It is an important problem in computer vision and an essential functionality in many imaging and graphics applications, e.g. object removal, image restoration, manipulation, re-targeting, compositing, and image-based rendering.

Source: High-Resolution Image Inpainting with Iterative Confidence Feedback and Guided Upsampling

Image source: High-Resolution Image Inpainting with Iterative Confidence Feedback and Guided Upsampling

Libraries

Use these libraries to find Image Inpainting models and implementations

Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models trained on Corrupted Data

utcsilab/ambient-diffusion-mri 13 Mar 2024

We open-source our code and the trained Ambient Diffusion MRI models: https://github. com/utcsilab/ambient-diffusion-mri .

5
13 Mar 2024

Efficient Diffusion Model for Image Restoration by Residual Shifting

zsyoaoa/resshift 12 Mar 2024

While diffusion-based image restoration (IR) methods have achieved remarkable success, they are still limited by the low inference speed attributed to the necessity of executing hundreds or even thousands of sampling steps.

466
12 Mar 2024

BrushNet: A Plug-and-Play Image Inpainting Model with Decomposed Dual-Branch Diffusion

tencentarc/brushnet 11 Mar 2024

Image inpainting, the process of restoring corrupted images, has seen significant advancements with the advent of diffusion models (DMs).

155
11 Mar 2024

PromptCharm: Text-to-Image Generation through Multi-modal Prompting and Refinement

ma-labo/promptcharm 6 Mar 2024

However, prompting remains challenging for novice users due to the complexity of the stable diffusion model and the non-trivial efforts required for iteratively editing and refining the text prompts.

4
06 Mar 2024

Matrix Completion with Convex Optimization and Column Subset Selection

ZAL-NASK/CSMC 4 Mar 2024

We present two algorithms that implement our Columns Selected Matrix Completion (CSMC) method, each dedicated to a different size problem.

3
04 Mar 2024

Diffusion Model-Based Image Editing: A Survey

siatmmlab/awesome-diffusion-model-based-image-editing-methods 27 Feb 2024

In this survey, we provide an exhaustive overview of existing methods using diffusion models for image editing, covering both theoretical and practical aspects in the field.

199
27 Feb 2024

HINT: High-quality INPainting Transformer with Mask-Aware Encoding and Enhanced Attention

chrischen1023/hint 22 Feb 2024

In this paper, we propose an end-to-end High-quality INpainting Transformer, abbreviated as HINT, which consists of a novel mask-aware pixel-shuffle downsampling module (MPD) to preserve the visible information extracted from the corrupted image while maintaining the integrity of the information available for high-level inferences made within the model.

9
22 Feb 2024

Text Image Inpainting via Global Structure-Guided Diffusion Models

blackprotoss/gsdm 26 Jan 2024

Leveraging the global structure of the text as a prior, the proposed GSDM develops an efficient diffusion model to recover clean texts.

20
26 Jan 2024

Robust Stochastically-Descending Unrolled Networks

smrhadou/robustunrolling 25 Dec 2023

To tackle these problems, we provide deep unrolled architectures with a stochastic descent nature by imposing descending constraints during training.

0
25 Dec 2023

HD-Painter: High-Resolution and Prompt-Faithful Text-Guided Image Inpainting with Diffusion Models

picsart-ai-research/hd-painter 21 Dec 2023

Recent progress in text-guided image inpainting, based on the unprecedented success of text-to-image diffusion models, has led to exceptionally realistic and visually plausible results.

197
21 Dec 2023