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--- |
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license: cc-by-2.0 |
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task_categories: |
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- image-classification |
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tags: |
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- face-recognition |
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- age-estimation |
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- gender-estimation |
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size_categories: |
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- 10k<n<100k |
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pretty_name: LAGENDA (LayerTeam Age and Gender Dataset) |
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--- |
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# LAGENDA Dataset |
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> This is a community mirror of the **LAGENDA** dataset created by **LayerTeam**. It has been uploaded here for easier access and integration with the Hugging Face `datasets` library. |
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> |
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> **All credit, rights, and accolades belong to the original authors.** Please see the citation section below. |
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## Dataset Description |
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**LAGENDA** (Large Age and Gender Dataset) is a dataset designed for age and gender recognition tasks. It addresses common biases in existing datasets by ensuring a near-perfect balance for all ages up to ~65 years. |
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* **Original Creator:** LayerTeam |
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* **Source:** [Original Project Page / GitHub](https://wildchlamydia.github.io/lagenda/) |
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* **Total Images:** 67,159 (sourced from Open Images Dataset) |
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* **Total Individuals:** 84,192 |
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* **Age Range:** 0 to 95 years |
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## Data Structure |
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The dataset includes images and an associated annotation structure (originally CSV) containing: |
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* `img_name`: The identifier of the image. |
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* `age`: Estimated age. |
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* `gender`: Estimated gender. |
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* `face_x0, face_y0, face_x1, face_y1`: Bounding box for the face. |
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* `person_x0, person_y0, person_x1, person_y1`: Bounding box for the person. |
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*(Note: values of -1 indicate no ground truth answer for that specific field).* |
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## License |
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The dataset is released under the **CC BY 2.0** license. |
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* You are free to share and adapt the material. |
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* Attribution is required. |
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## Citation |
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```bibtex |
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@article{mivolo2023, |
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Author = {Maksim Kuprashevich and Irina Tolstykh}, |
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Title = {MiVOLO: Multi-input Transformer for Age and Gender Estimation}, |
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Year = {2023}, |
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Eprint = {arXiv:2307.04616}, |
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} |
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@article{mivolo2024, |
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Author = {Maksim Kuprashevich and Grigorii Alekseenko and Irina Tolstykh}, |
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Title = {Beyond Specialization: Assessing the Capabilities of MLLMs in Age and Gender Estimation}, |
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Year = {2024}, |
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Eprint = {arXiv:2403.02302}, |
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} |
