Image Restoration
464 papers with code • 1 benchmarks • 12 datasets
Image Restoration is a family of inverse problems for obtaining a high quality image from a corrupted input image. Corruption may occur due to the image-capture process (e.g., noise, lens blur), post-processing (e.g., JPEG compression), or photography in non-ideal conditions (e.g., haze, motion blur).
Libraries
Use these libraries to find Image Restoration models and implementationsDatasets
SIDD
CBSD68
Raindrop
PIRM
TinyPerson
Real Rain Dataset
UHDM
Fingerprint inpainting and denoising
Subtasks
Latest papers with no code
AdaIR: Exploiting Underlying Similarities of Image Restoration Tasks with Adapters
Towards this goal, we propose AdaIR, a novel framework that enables low storage cost and efficient training without sacrificing performance.
Improving Bracket Image Restoration and Enhancement with Flow-guided Alignment and Enhanced Feature Aggregation
In this paper, we address the Bracket Image Restoration and Enhancement (BracketIRE) task using a novel framework, which requires restoring a high-quality high dynamic range (HDR) image from a sequence of noisy, blurred, and low dynamic range (LDR) multi-exposure RAW inputs.
Referring Flexible Image Restoration
These situations and requirements shed light on a new challenge in image restoration, where a model must perceive and remove specific degradation types specified by human commands in images with multiple degradations.
OmniSSR: Zero-shot Omnidirectional Image Super-Resolution using Stable Diffusion Model
Omnidirectional images (ODIs) are commonly used in real-world visual tasks, and high-resolution ODIs help improve the performance of related visual tasks.
Joint Conditional Diffusion Model for Image Restoration with Mixed Degradations
Image restoration is rather challenging in adverse weather conditions, especially when multiple degradations occur simultaneously.
STAIC regularization for spatio-temporal image reconstruction
We propose a regularization-based image restoration scheme for 2D images recorded over time (2D+t).
Empowering Image Recovery_ A Multi-Attention Approach
Integration of attention mechanisms across feature and positional dimensions further enhances the recovery of fine details.
DiffBody: Human Body Restoration by Imagining with Generative Diffusion Prior
Human body restoration plays a vital role in various applications related to the human body.
GAMA-IR: Global Additive Multidimensional Averaging for Fast Image Restoration
The network is a simple shallow network with an efficient block that implements global additive multidimensional averaging operations.
IPT-V2: Efficient Image Processing Transformer using Hierarchical Attentions
Recent advances have demonstrated the powerful capability of transformer architecture in image restoration.
