Downloads · 30 days
0
kartiknarayan/facexformer
facexformer is a any-to-any model from kartiknarayan. Use it for the any-to-any task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
Downloads · 30 days
0
Access
Public
Updated Apr 29, 2025
Repo size
2.1 GB
Likes
10
Public
Click a slice to open those files.
.pt1.1 GB · 100%
From the Hugging Face model README
Project Page | Paper (ArXiv) | Code
</div>FaceXFormer is an end-to-end unified model capable of handling a comprehensive range of facial analysis tasks such as face parsing, landmark detection, head pose estimation, attributes prediction, age/gender/race estimation, facial expression recognition and face visibility prediction.
<div align="center"> <img src='assets/intro.png'> </div>FaceXFormer is a transformer-based encoder-decoder architecture where each task is treated as a learnable token, enabling the integration of multiple tasks within a single framework.
<div align="center"> <img src='assets/main_archi.png'> </div>The models can be downloaded directly from this repository or using python:
from huggingface_hub import hf_hub_download
hf_hub_download(repo_id="kartiknarayan/facexformer", filename="ckpts/model.pt", local_dir="./")
@article{narayan2024facexformer,
title={FaceXFormer: A Unified Transformer for Facial Analysis},
author={Narayan, Kartik and VS, Vibashan and Chellappa, Rama and Patel, Vishal M},
journal={arXiv preprint arXiv:2403.12960},
year={2024}
}
Please check our GitHub repository for complete inference instructions.