ABSTRACT
No abstract available.
- Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, and Timo Aila. 2020. Analyzing and improving the image quality of StyleGAN. In Proc. CVPR. 8110–8119.Google Scholar
Cross Ref
- Daniel Roich, Ron Mokady, Amit H Bermano, and Daniel Cohen-Or. 2021. Pivotal Tuning for Latent-based Editing of Real Images. arXiv preprint arXiv:2106.05744(2021).Google Scholar
- Tao Yang, Peiran Ren, Xuansong Xie, and Lei Zhang. 2021. GAN Prior Embedded Network for Blind Face Restoration in the Wild. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 672–681.Google Scholar
Cross Ref
- Shengyu Zhao, Zhijian Liu, Ji Lin, Jun-Yan Zhu, and Song Han. 2020. Differentiable augmentation for data-efficient gan training. arXiv preprint arXiv:2006.10738(2020).Google Scholar
Recommendations
DAGP-Face Restorer: Blind Face Restoration Network with Domain-aligned Generative Prior
ICCAI '23: Proceedings of the 2023 9th International Conference on Computing and Artificial IntelligenceBlind face restoration is an extremely challenging task since it often relies on suitable reference priors, which are unavailable in real-world scenarios. Generative prior encapsulated in pre-trained face generator has shown its effectiveness in ...
Pose-invariant features and personalized correspondence learning for face recognition
In surveillance systems, face recognition plays an important role for human identification. In such systems, human faces are spatially unconstrained, which results in a significant change in pose, and face recognition becomes more challenging when only ...
Propagating Facial Prior Knowledge for Multitask Learning in Face Super-Resolution
Existing face hallucination methods always achieve improved performance through regularizing the model with facial prior. Most of them always estimate facial prior information first and then leverage it to help the prediction of the target high-resolution ...





Comments