This repository serves as a comprehensive, curated collection of resources for super-resolution research, including papers, datasets, and code repositories. It targets researchers and engineers in the field, offering a centralized point for tracking advancements and accessing implementations, thereby accelerating development and adoption of new techniques.

How It Works

The project functions as a dynamic, organized index of super-resolution literature and code. It categorizes resources primarily by publication year and methodology (e.g., Deep Learning-based, Non-DL-based), with specific sections for workshops and surveys. This structured approach allows users to quickly navigate the evolving landscape of super-resolution research and identify relevant state-of-the-art solutions.

Quick Start & Requirements

This repository is a curated list of external resources and does not contain executable code or a unified installation process. Users must refer to individual linked repositories for their specific setup instructions, dependencies (e.g., Python versions, CUDA, specific libraries), and hardware requirements.

Highlighted Details

• Features recent advancements, with a significant focus on 2026 publications from top-tier conferences like CVPR, ICLR, and AAAI.
• Highlights diverse methodologies, including diffusion models (e.g., Ada-RefSR, LiveMoments, VOSR, FiDeSR), transformers (e.g., SAT, UCAN, OmniFM), GANs, and CNNs.
• Includes specialized areas such as real-world super-resolution (e.g., Real-IISR, DACESR), video super-resolution (e.g., DUO-VSR, CDA-VSR), and specific applications like medical imaging (OmniFM, XA-SSL) and underwater enhancement.

Maintenance & Community

Information regarding maintainers, community channels (e.g., Discord, Slack), or active development status beyond "in progress" is not detailed in the provided README.

Licensing & Compatibility

No specific open-source license is mentioned for the repository itself. Users should verify the licenses of individual linked code repositories for compatibility with their intended use cases.

Limitations & Caveats

The repository is explicitly marked as "in progress," indicating ongoing curation and potential for incomplete or outdated entries. As a collection, it lacks a unified API or direct executability, requiring users to engage with numerous external projects. The rapid pace of super-resolution research means continuous updates are necessary to maintain relevance.