This repository serves as a comprehensive, curated collection of state-of-the-art research papers, datasets, and tools related to face technology. It targets researchers, engineers, and practitioners in computer vision and AI, providing a centralized resource for advancements in face detection, recognition, alignment, generation, and manipulation.

How It Works

The repository is structured by sub-fields within face technology, categorizing papers and datasets by their primary focus (e.g., Face Recognition, Face Detection, Face Generation). It acts as a literature review and resource aggregator, linking to official papers, code repositories, and datasets, enabling users to quickly find relevant and cutting-edge work.

Quick Start & Requirements

• Installation: No direct installation required; it's a curated list of external resources.
• Prerequisites: Access to the internet to view linked papers, code, and datasets. Some linked code may require specific Python versions, deep learning frameworks (PyTorch, TensorFlow, MXNet), and potentially GPUs.
• Resources: Browsing the repository is lightweight. However, downloading datasets or running linked code can require significant storage, computational power (especially GPUs), and time.
• Links:
  • Website: https://becauseofAI.github.io/HelloFace
  • Face Benchmark and Dataset: https://becauseofAI.github.io/HelloFace/#/FaceBenchmarkandDataset
  • Face Recognition: https://becauseofAI.github.io/HelloFace/#/FaceRecognition
  • Face Detection: https://becauseofAI.github.io/HelloFace/#/FaceDetection
  • Face Landmark: https://becauseofAI.github.io/HelloFace/#/FaceLandmark
  • Face 3D: https://becauseofAI.github.io/HelloFace/#/Face3D
  • Face GAN: https://becauseofAI.github.io/HelloFace/#/FaceGAN

Highlighted Details

• Extensive coverage of papers from major conferences (CVPR, ICCV, ECCV, IJCAI, AAAI, SIGGRAPH).
• Detailed lists of datasets for various face tasks, including scale and image counts.
• Links to implementations for many listed papers, facilitating reproducibility.
• Categorization includes niche areas like Face De-Occlusion, Face Aging, and Face Anti-Spoofing.

Maintenance & Community

• The repository indicates recent updates (as of April 2022), suggesting ongoing curation.
• The website is open for contributions via pull requests, indicating a community-driven aspect.

Licensing & Compatibility

• Licensing is not specified for the repository itself.
• Linked papers and code are subject to their respective licenses. Many research codebases are released under permissive licenses (MIT, Apache 2.0), but some may have non-commercial restrictions or require specific academic use.

Limitations & Caveats

• This is a curated list, not a unified framework or library; users must interact with external resources.
• The "SOTA" (State-of-the-Art) claims are based on the inclusion of recent papers, but direct performance comparisons or benchmarks are not provided within this repository itself.
• The last major update appears to be from April 2022, so it may not reflect the absolute latest research published since then.