--- 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} } ```