Transformers
PyTorch
face-recognition
face-generation
face-segmentation
generative-adversarial-network
Instructions to use NimaBoscarino/aot-gan-celebahq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NimaBoscarino/aot-gan-celebahq with Transformers:
# Load model directly from transformers import InpaintGenerator model = InpaintGenerator.from_pretrained("NimaBoscarino/aot-gan-celebahq", dtype="auto") - Notebooks
- Google Colab
- Kaggle
metadata
tags:
- face-recognition
- face-generation
- face-segmentation
- generative-adversarial-network
metrics:
- L1
- PSNR
- SSIM
- FID
datasets:
- celeba-hq
AOT-GAN CelebA-HQ
AOT-GAN is a model that can be used for image in-painting. The CelebA-HQ checkpoint is trained on synthetic human faces, which should make it suitable for touching up and restoring portraits.
This model was generated using AOT-GAN-for-Inpainting, cited as
@inproceedings{yan2021agg,
author = {Zeng, Yanhong and Fu, Jianlong and Chao, Hongyang and Guo, Baining},
title = {Aggregated Contextual Transformations for High-Resolution Image Inpainting},
booktitle = {Arxiv},
pages={-},
year = {2020}
}
Dataset
The CelebA-HQ dataset was created with this codebase: https://github.com/tkarras/progressive_growing_of_gans, owned by NVidia and licensed under Creative Commons Attribution-NonCommercial 4.0 International.