F2RPC: Fake to Real Portrait Control From a Virtual Character-Reference-Cited by-同舟云学术

F2RPC: Fake to Real Portrait Control From a Virtual Character

Published:2023 Issue: Volume:11 Page:92120-92134
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Kang Seoungyoon¹^ORCID,Kim Minjae²^ORCID,Shim Hyunjung³^ORCID

Affiliation:

1. School of Integrated Technology, Yonsei University, Yeonsu-gu, Incheon, Republic of Korea

2. Vision AI Laboratory, AI Center, NCSOFT, Gyeonggi, Seongnam, Republic of Korea

3. Kim Jaechul Graduate School of Artificial Intelligence, Korea Advanced Institute of Science and Technology (KAIST), Dongdaemun-gu, Seoul, Republic of Korea

Funder

NCSOFT, Seongnam, South Korea

Basic Science Research Program through the National Research Foundation of Korea

MSIP

IITP grant funded the Korea Government

KEIT grant funded by the Korea Government

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10225329.pdf?arnumber=10225329

Reference53 articles.

1. A 3D Morphable Model Learnt from 10,000 Faces

2. X2Face: A Network for Controlling Face Generation Using Images, Audio, and Pose Codes

3. PIRenderer: Controllable Portrait Image Generation via Semantic Neural Rendering

4. HeadGAN: One-shot Neural Head Synthesis and Editing

5. ArcFace: Additive Angular Margin Loss for Deep Face Recognition

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Novel Approach to Detect Face Fraud Detection Using Artificial Intelligence;2024 Second International Conference on Emerging Trends in Information Technology and Engineering (ICETITE);2024-02-22