Paper¶

PrimateFace: Cross-Species Primate Facial Analysis¶

Our research presents novel methods for advanced primate facial analysis across multiple species.

Abstract¶

Coming soon - our paper is currently under review.

Key Contributions¶

1. Cross-Species Dataset: The largest annotated dataset of primate faces spanning multiple species
2. Unified Architecture: A single model architecture that generalizes across primate species
3. Benchmark Results: State-of-the-art performance on primate face detection and landmark localization
4. Open Source Tools: Complete pipeline for primate facial analysis research

Methods¶

Architecture¶

Our approach uses a multi-task learning framework that jointly optimizes for: - Face detection - Landmark localization
- Species classification

Training Data¶

• Dataset size and composition details
• Annotation methodology
• Quality control procedures

Evaluation¶

Comprehensive evaluation across: - Multiple primate species - Various lighting conditions - Different poses and expressions - Wild vs. captive settings

Results¶

Performance metrics and comparisons will be available upon publication.

Preprint¶

The preprint will be available on arXiv soon.

Citation¶

@article{primateface2024,
  title={PrimateFace: Cross-Species Primate Facial Analysis},
  author={Your Authors},
  journal={In Review},
  year={2024}
}

Supplementary Materials¶

Additional results, visualizations, and implementation details will be available with the paper release.

Contact¶

For questions about the paper, contact: primateface@gmail.com