Wenzhe Zhai
Biographic Data
| ID | 10055064 |
|---|---|
| NAME | Wenzhe Zhai |
| GIVEN NAMES | Wenzhe |
| FAMILY NAME | Zhai |
| SIGNATURE | ZHAI W |
| AFFILIATIONS | Shandong University of Technology |
| ORCID | 0000-0003-0996-6832 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Training-Free 3-D Face Avatars Generation by Knowledge Discovering in Foundational Models
An informative 3-D avatar, closely mirroring real-world traits, plays a pivotal role in accessing the metaverse. Traditional methods for creating 3-D avatars usually employ one-to-one training, which restricts avatar diversity. To enhance style diversity in generated 3-D avatars, we utilize synthesized images derived with prompts from ChatGPT in a conversational manner, ultimately resulting in a broader range of 3-D variations. Rather than creati…
Defending Deepfakes by Saliency-Aware Attack
With the rapid development of deep learning, especially the generative adversarial network (GAN), face modification has been substantially advanced and enables the generated images to look more realistic. Given an image or a video frame of a person, such a system can create fake images, which manipulates the movement, expression, and even appearance, e.g., hair color, eye color, and age. Such a system is termed Deepfake, which has raised signific…
No prominent works on this page.
Defending Deepfakes by Saliency-Aware Attack
With the rapid development of deep learning, especially the generative adversarial network (GAN), face modification has been substantially advanced and enables the generated images to look more realistic. Given an image or a video frame of a person, such a system can create fake images, which manipulates the movement, expression, and even appearance, e.g., hair color, eye color, and age. Such a system is termed Deepfake, which has raised signific…
Training-Free 3-D Face Avatars Generation by Knowledge Discovering in Foundational Models
An informative 3-D avatar, closely mirroring real-world traits, plays a pivotal role in accessing the metaverse. Traditional methods for creating 3-D avatars usually employ one-to-one training, which restricts avatar diversity. To enhance style diversity in generated 3-D avatars, we utilize synthesized images derived with prompts from ChatGPT in a conversational manner, ultimately resulting in a broader range of 3-D variations. Rather than creati…
Artificial Intelligence (2 works) · Computer Science (2 works) · 3D Shape Modeling and Analysis (1 work) · Adversarial Robustness in Machine Learning (1 work) · Augmented Reality Applications (1 work) · Cognitive science (1 work) · Computer security (1 work) · Face recognition and analysis (1 work) · Generative Adversarial Networks and Image Synthesis (1 work) · Geography (1 work)