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---
pretty_name: RareFace-50
license: cc-by-nc-4.0
tags:
- faces
- personalization
- avatars
- talking-head
- youtube
---
# RareFace-50 (from Low-Rank Head Avatar Personalization with Registers)
Dataset for [Low-Rank Head Avatar Personalization with Registers](https://openreview.net/pdf?id=mhARf5VzCn). Also available on [arxiv](https://arxiv.org/abs/2506.01935).
[Project Page](https://starc52.github.io/publications/2025-05-28-LoRAvatar/)
## Dataset Summary
RareFace-50 is a curated collection of **challenging human faces** intended for evaluating personalization of talking-head and avatar generation methods.
Unlike many existing face video datasets that focus primarily on celebrities and well-known public figures (e.g., television personalities), RareFace-50 deliberately targets **underrepresented facial appearances**, with an emphasis on:
- **Distinctive facial details** (e.g., pronounced wrinkles, unique tattoos, scars, or other high-frequency details),
- **Wide variation in age and appearance**,
- **High-resolution, close-up footage**.
The dataset is constructed from **50 identities**, each with **2 short clips**, for a total of **100 clips**. Source videos are high-resolution interview-style recordings (1080p, 2K, and 4K) collected from YouTube public broadcasts. The average duration of each clip is around **15 seconds**.
> **Important:**
> This repository contains **only metadata** about the clips (YouTube links and temporal trim information) in a CSV file.
---
## Dataset Structure
### Files
The dataset is provided as a **single CSV file** in this repository (`RareFace50.csv`).
Each row corresponds to a **two clip** and includes:
- A YouTube link for the source video.
- Two start times and end times defining the clips within that video.
> **Timestamp format:** All temporal fields are stored as strings in `h:mm:ss` format
> (e.g., `0:00:13`, `0:01:05`, `1:23:45`).
### Schema
- `youtube_url` (string)
Full YouTube URL for the source video.
- `start_time` (string)
Clip start time in `h:mm:ss`.
- `end_time` (string)
Clip end time in `h:mm:ss`.
---
## How to Use
### Loading the CSV
You can access the CSV directly using Python’s standard tools or `datasets`:
```python
from datasets import load_dataset
ds = load_dataset("StonyBrook-CVLab/RareFace-50")
print(ds["train"][0])
```
If you use this dataset, please be so kind to cite us:
```
@inproceedings{
chakkera2025lowrank,
title={Low-Rank Head Avatar Personalization with Registers},
author={Sai Tanmay Reddy Chakkera and Aggelina Chatziagapi and Md Moniruzzaman and Chen-ping Yu and Yi-Hsuan Tsai and Dimitris Samaras},
booktitle={The Thirty-ninth Annual Conference on Neural Information Processing Systems},
year={2025},
url={(https://openreview.net/pdf?id=mhARf5VzCn)}
}
``` |