This repository is a curated list of "Papers With Code" (PWC) entries, primarily focusing on computer vision and machine learning research. It serves as a valuable resource for researchers and practitioners looking to find papers with corresponding code implementations, sorted by popularity (stars).

How It Works

The repository compiles links to research papers (often from arXiv or conference proceedings) and their associated code repositories (typically on GitHub). Entries are organized by year and include details like the paper title, conference, code repository link, and the number of stars the code repository has received, indicating community interest and adoption.

Quick Start & Requirements

This repository is a data collection and does not require installation or execution. Users can simply browse the README for links to papers and code.

Highlighted Details

• Comprehensive PWC Collection: Covers a wide range of influential papers across various computer vision and ML conferences.
• Star-Based Popularity: Sorting by stars provides a quick indicator of community adoption and perceived importance.
• Weekly Updates: The project aims for continuous updates, ensuring a relatively current snapshot of PWC.
• Community Driven: Suggestions for new conferences or papers can be made via GitHub issues.

Maintenance & Community

The project appears to be maintained by a single individual, @fvzaur, who actively encourages community contributions and suggestions.

Licensing & Compatibility

The repository itself does not host code, so licensing is determined by the individual linked projects. Compatibility for commercial use or closed-source linking depends entirely on the licenses of those external repositories.

Limitations & Caveats

The repository is explicitly marked as "no longer maintained," meaning updates have ceased. The data reflects the state of "Papers With Code" as of the last update, which may not include the most recent research.