This repository provides a GitHub Actions workflow to automatically update CV papers daily. It is designed for researchers and academics interested in the latest publications in computer vision, specifically in areas like SLAM, SFM, visual localization, keypoint detection, image matching, and NeRF. The primary benefit is staying current with a curated list of new research papers.

How It Works

The project leverages GitHub Actions to periodically scrape arXiv for new papers related to specified computer vision topics. It then formats this information into a structured table, including publication date, title, authors, arXiv ID, and links to PDFs and code (if available). This automated process ensures a regularly updated bibliography for the community.

Quick Start & Requirements

• Primary install / run command: No direct installation is required as this is a GitHub Actions workflow. The workflow runs automatically on a schedule.
• Prerequisites: A GitHub account is needed to view and potentially fork the repository.
• Links:
  • Usage instructions: here
  • Table of Contents: here

Highlighted Details

• Automatically updates a list of computer vision papers from arXiv.
• Covers key areas like SLAM, SFM, visual localization, keypoint detection, image matching, and NeRF.
• Formats findings into a structured table with direct links.
• Leverages GitHub Actions for automated execution.

Maintenance & Community

• The repository is maintained by Vincentqyw.
• Community interaction details (e.g., Discord/Slack) are not explicitly mentioned in the README.

Licensing & Compatibility

• The repository's license is not specified in the provided README snippet.

Limitations & Caveats

• The accuracy of code links depends on whether authors provide them on arXiv.
• The workflow relies on arXiv's API and structure, which could change.