A Simple Baseline for StyleGAN Inversion

By Tianyi Wei, Dongdong Chen, Wenbo Zhou, Jing Liao, Weiming Zhang, Lu Yuan, Gang Hua, Nenghai Yu. 2021

34 citations recorded by the source corpus.

Subfields: Generative Models

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Generative Models

1. Yujiu Yang
2. Weihao Xia
3. Jing-Hao Xue
4. Ming-Hsuan Yang
5. Yulun Zhang
6. Qifeng Chen
7. Anh Tuan Tran
8. Binh-Son Hua

Citations in the corpus

• GAN Inversion: A Survey (2021, background): “[32] find 18 mapping modules unnecessary and propose a very simple and efficient head, which just consists of an average pooling layer and a fully connected layer.”
• High-Fidelity GAN Inversion for Image Attribute Editing (2021, background): “[38] improved the inversion efficiency by a shallow network with efficient heads.”
• HyperInverter: Improving StyleGAN Inversion via Hypernetwork (2021, methodology): “Specially, our work can be further improved by applying iterative refinement [3], multi-layer identity loss [49], or extending to StyleGAN3 [26].”