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.directory | ||
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models/pretrained/ | ||
datasets/ | ||
experiments/ |
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# FALCO: Attribute-preserving Face Dataset Anonymization via Latent Code Optimization. | ||
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Authors official PyTorch implementation of the [Attribute-preserving **F**ace Dataset **A**nonymization via **L**atent **C**ode **O**ptimization (CVPR 2023)](TODO). If you find this code useful for your research, please [cite]() our paper. | ||
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# Code to appear soon... | ||
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# Citation | ||
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[1] Simone Barattin, Christos Tzelepis, Ioannis Patras, Nicu Sebe, "Attribute-preserving Face Dataset Anonymization via Latent Code Optimization", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023. | ||
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Bibtex entry: | ||
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```bibtex | ||
@InProceedings{falco2023cvpr, | ||
author = {Barattin, Simone and Tzelepis, Christos and Patras, Ioannis and Sebe, Nicu}, | ||
title = {Attribute-preserving Face Dataset Anonymization via Latent Code Optimization}, | ||
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, | ||
month = {June}, | ||
year = {2023}, | ||
} | ||
``` | ||
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## Acknowledgment | ||
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This research was supported by the EU's Horizon 2020 programme H2020-951911 [AI4Media](https://www.ai4media.eu/) project. | ||
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