Discrepancy-Aware Meta-Learning for Zero-Shot Face Manipulation Detection-Reference-Cited by-同舟云学术

Discrepancy-Aware Meta-Learning for Zero-Shot Face Manipulation Detection

Published:2023 Issue: Volume:32 Page:3759-3773
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Yu Bingyao¹^ORCID,Li Xiu¹^ORCID,Li Wanhua²^ORCID,Zhou Jie²^ORCID,Lu Jiwen²^ORCID

Affiliation:

1. Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China

2. Department of Automation, State Key Laboratory of Intelligent Technologies and Systems, Beijing Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China

Funder

National Key Research and Development Program of China

Shenzhen Science and Technology Project

Shenzhen Stability Support Plan Project

National Natural Science Foundation of China

Grant from the Beijing Academy of Artificial Intelligence

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/83/9991910/10173741.pdf?arnumber=10173741

Reference77 articles.

1. StarGAN: Unified Generative Adversarial Networks for Multi-domain Image-to-Image Translation

2. Prototypical Siamese Networks for Few-shot Learning

3. MagDR: Mask-guided Detection and Reconstruction for Defending Deepfakes

4. Detecting Deepfakes with Self-Blended Images

5. FakeCatcher: Detection of Synthetic Portrait Videos using Biological Signals

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