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# PALM: A Dataset and Baseline for Learning Multi-subject Hand Prior ([Paper](https://arxiv.org/abs/2511.05403))

[Zicong Fan](https://zc-alexfan.github.io/), [Edoardo Remelli](https://scholar.google.com/citations?user=yz2P_aUAAAAJ&hl=en), David Dimond, [Fadime Sener](https://scholar.google.com/citations?user=-juoweoAAAAJ&hl=en), [Liuhao Ge](https://scholar.google.com/citations?user=PTsnx5gAAAAJ&hl=en), [Bugra Tekin](https://btekin.github.io/), [Cem Keskin](https://scholar.google.com/citations?user=9HoiYnYAAAAJ&hl=en), [Shreyas Hampali](https://shreyashampali.github.io/)

Github Repo: [https://github.com/facebookresearch/PALM](https://github.com/facebookresearch/PALM)

<p align="center">
    <img src="./dataset-teaser.jpg" alt="Image" width="100%" />
</p>

This is a repository for PALM, a large-scale dataset comprising calibrated multi-view high-resolution RGB images and 3dMD hand scans (a). It features 263 subjects spanning a wide range of skin tones and hand sizes, 90k RGB images, and 13k high-quality hand scans with corresponding MANO registrations (b). This diversity and precision provide a foundation for learning a universal prior over human hand shape and appearance.

### Why use PALM?

Summary on dataset:

- 90k multi-view RGB images
- Accurate MANO registration
- 263 subjects
- 7 RGB views
- 2448 x 2048 high resolution images
- 13k 3dMD hand scans