In-Domain GAN Inversion for Faithful Reconstruction and Editability
Generative Adversarial Networks (GANs) have significantly advanced image synthesis through mapping randomly sampled latent codes to high-fidelity synthesized images. However, applying well-trained GANs to real image editing remains challenging. A common solution is to find an approximate latent code...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 46(2024), 5 vom: 01. Apr., Seite 2607-2621
|
|---|
| 1. Verfasser: |
Zhu, Jiapeng
(VerfasserIn) |
|---|
| Weitere Verfasser: |
Shen, Yujun,
Xu, Yinghao,
Zhao, Deli,
Chen, Qifeng,
Zhou, Bolei |
|---|
| Format: | Online-Aufsatz
|
|---|
| Sprache: | English |
|---|
| Veröffentlicht: |
2024
|
|---|
| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
|
|---|
| Schlagworte: | Journal Article |
|---|