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---
license: unknown
---

# FakeParts: A New Family of AI-Generated DeepFakes

![HF Downloads](https://img.shields.io/badge/HF%20Downloads-2k-green)
![Python Version](https://img.shields.io/badge/python-%3E%3D3.10-blue)
[![Code Style: Black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
[![License](https://img.shields.io/badge/License-BSD_3--Clause-blue.svg)](https://opensource.org/licenses/BSD-3-Clause)
[![Hugging Face Dataset](https://img.shields.io/badge/Hugging%20Face-Space-yellow)](https://huggingface.co/datasets/hi-paris/FakeParts)
[![arXiv](https://img.shields.io/badge/arXiv-2508.21052-red.svg)](https://arxiv.org/abs/2508.21052)


> **FakeParts** are *partial* deepfakes—localized spatial or temporal edits that blend into otherwise real videos.
> 
> **FakePartsBench** is the first benchmark purpose-built to evaluate them.
> 

## Our paper

```
@misc{brison2025fakeparts,
    title={FakeParts: a New Family of AI-Generated DeepFakes},
    author={Gaetan Brison and Soobash Daiboo and Samy Aimeur and Awais Hussain Sani and Xi Wang and Gianni Franchi and Vicky Kalogeiton},
    year={2025},
    eprint={2508.21052},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}
```