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metadata 
license: cc-by-nc-4.0
gated: manual
extra_gated_heading: Request access to PrimateFace
extra_gated_description: >-
  This dataset contains images of primates with facial landmark annotations.
  Please fill out the form below and our team will review your request within
  2-3 business days.
extra_gated_prompt: >-
  By requesting access, you agree to use this dataset for non-commercial
  research purposes only and to comply with all applicable institutional and
  ethical guidelines.
extra_gated_fields:
  Full Name: text
  Email: text
  Organization: text
  Intended Use:
    type: select
    options:
      - Academic Research
      - Education
      - label: Other
        value: other
  I agree to use this dataset for non-commercial research ONLY:
    type: checkbox
extra_gated_button_content: Submit access request

PrimateFace

Cross-species primate face analysis dataset with facial landmark annotations for non-human primates. The dataset provides annotations in two landmark conventions, enabling landmark conversion across schemes.

Landmark Conventions

PrimateFace supports two facial landmark configurations on the same images:

  • COCO 68-landmark (dlib68): The standard dlib/COCO Whole-Body face keypoint layout (jaw contour, eyebrows, nose, eyes, mouth).
  • PrimateFace 48-landmark (pf48): A custom primate-optimized landmark set.

Configs

Each config corresponds to a data source and annotation variant:

Config Keypoints Description
mac-au-68kpt 68 (dlib/COCO) Cayo Santiago action-unit videos, COCO Whole-Body face landmarks
mac-au-48kpt 48 (PrimateFace) Cayo Santiago action-unit videos, PrimateFace custom landmarks

Both configs contain the same images annotated with different landmark sets.

Usage 

from datasets import load_dataset

# Load 68-keypoint annotations (dlib/COCO convention)
ds_68 = load_dataset("fparodi/PrimateFace", "mac-au-68kpt")

# Load 48-keypoint annotations (PrimateFace convention)
ds_48 = load_dataset("fparodi/PrimateFace", "mac-au-48kpt")

Citation

If you use this dataset, please cite:

@article{parodi2025primateface,
  title={PrimateFace: A Machine Learning Resource for Automated Face Analysis in Human and Non-human Primates},
  url={https://www.biorxiv.org/content/10.1101/2025.08.12.669927},
  year={2025}
}

Links

License

CC-BY-NC-4.0 — non-commercial research use only.