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--- |
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license: mit |
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tags: |
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- transformers |
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language: |
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- en |
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--- |
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# FaceXFormer Model Card |
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<div align="center"> |
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[**Project Page**](https://kartik-3004.github.io/facexformer_web/) **|** [**Paper (ArXiv)**](https://arxiv.org/abs/2403.12960) **|** [**Code**](https://github.com/Kartik-3004/facexformer) |
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</div> |
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## Introduction |
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FaceXFormer is an end-to-end unified model capable of handling a comprehensive range of facial analysis tasks such as face parsing, |
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landmark detection, head pose estimation, attributes recognition, age/gender/race estimation and landmarks visibility prediction. |
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<div align="center"> |
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<img src='assets/intro_viz.png'> |
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</div> |
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## Model Details |
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FaceXFormer is a transformer-based encoder-decoder architecture where each task is treated as a learnable token, enabling the |
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integration of multiple tasks within a single framework. |
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<div align="center"> |
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<img src='assets/main_archi.png'> |
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</div> |
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## Usage |
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The models can be downloaded directly from this repository or using python: |
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```python |
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from huggingface_hub import hf_hub_download |
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hf_hub_download(repo_id="kartiknarayan/facexformer", filename="ckpts/model.pt", local_dir="./") |
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``` |
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## Citation |
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```bibtex |
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@article{narayan2024facexformer, |
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title={FaceXFormer: A Unified Transformer for Facial Analysis}, |
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author={Narayan, Kartik and VS, Vibashan and Chellappa, Rama and Patel, Vishal M}, |
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journal={arXiv preprint arXiv:2403.12960}, |
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year={2024} |
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} |
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``` |
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Please check our [GitHub repository](https://github.com/Kartik-3004/facexformer) for complete inference instructions. |
