This repository serves as an "Awesome List" for crowd counting, aggregating datasets, papers, leaderboards, and code related to the field. It's a valuable resource for researchers and practitioners looking to stay updated on state-of-the-art methods and benchmarks in crowd analysis.

How It Works

The project curates a comprehensive collection of resources, categorizing them by datasets, papers (with links to arXiv and code), challenges, and technical blogs. It provides leaderboards with performance metrics (MAE, MSE) for various datasets, allowing users to compare different crowd counting models. The inclusion of recent papers and datasets indicates an active effort to keep the list current.

Quick Start & Requirements

This repository is a curated list and does not have a direct installation or execution command. Users can browse the links provided for datasets, papers, and code repositories, which will have their own specific setup instructions and dependencies (e.g., Python, PyTorch, TensorFlow, specific libraries).

Highlighted Details

• Extensive collection of papers, including recent advancements and seminal works in crowd counting.
• Detailed leaderboards with performance metrics across multiple benchmark datasets (ShanghaiTech Part A/B, JHU-CROWD++, UCF-QNRF, WorldExpo'10, UCSD, Mall).
• Links to associated code repositories for many of the listed papers, facilitating reproducibility and experimentation.
• Information on recent datasets and ongoing challenges in the field.

Maintenance & Community

The repository is maintained by gjy3035. The "Awesome List" format suggests community contributions are welcome via issues and pull requests. Links to technical blogs and discussions are provided, fostering community engagement.

Licensing & Compatibility

The repository itself is likely under a permissive license (e.g., MIT, Apache 2.0) as is common for "Awesome Lists." However, the licensing of the linked datasets, papers, and code repositories will vary and must be checked individually.

Limitations & Caveats

As a curated list, the repository's primary limitation is its reliance on external links. The accuracy and availability of linked resources are subject to change. The "Awesome List" format means it's a collection rather than a unified framework, requiring users to navigate and integrate individual components.