This repository provides a comprehensive, categorized collection of papers accepted to CVPR 2024, aimed at researchers and practitioners in computer vision. It offers a structured overview of the latest advancements across numerous subfields, facilitating efficient discovery and exploration of cutting-edge research.

How It Works

The project acts as a curated index, organizing CVPR 2024 papers by topic. It leverages a detailed taxonomy covering areas from fundamental image processing tasks like segmentation and super-resolution to advanced domains such as 3D reconstruction, autonomous driving, and vision-language models. The categorization allows users to quickly navigate and identify relevant research within specific areas of interest.

Quick Start & Requirements

• Access: Browse the categorized list directly within the GitHub repository.
• Requirements: No specific software installation is required; access is via a web browser.
• Links: Official CVPR 2024 website: https://cvpr.thecvf.com/

Highlighted Details

• Comprehensive categorization of all CVPR 2024 papers.
• Includes links to official paper pages and, where available, associated code and project pages.
• Highlights Best Papers, Best Paper Runners-Up, and Best Student Papers.
• Covers a wide spectrum of computer vision sub-fields, from traditional tasks to emerging areas.

Maintenance & Community

• The repository is actively maintained, with recent updates indicating the completion of paper categorization.
• Community interaction is likely through GitHub issues and pull requests.

Licensing & Compatibility

• The repository itself is likely under a permissive license (e.g., MIT), but the underlying papers are subject to their respective copyright and publication terms.

Limitations & Caveats

This repository is a curated list and does not host the papers themselves. Access to full paper content requires visiting the official CVPR publication site. The categorization is based on the project maintainers' interpretation and may not perfectly align with every reader's specific needs.