7 citations · 16 across the 8 of their papers we have counts for
4 papers · 2 filters
Self-supervised GAN Detector
Yonghyun Jeong, Doyeon Kim, Pyounggeon Kim +2
Although the recent advancement in generative models brings diverse advantages to society, it can also be abused with malicious purposes, such as fraud, defamation, and fake news.…
MToFNet: Object Anti-Spoofing with Mobile Time-of-Flight Data
Yonghyun Jeong, Doyeon Kim, Jaehyeon Lee +3
In online markets, sellers can maliciously recapture others' images on display screens to utilize as spoof images, which can be challenging to distinguish in human eyes. To prevent…
Observations on K-image Expansion of Image-Mixing Augmentation for Classification
Joonhyun Jeong, Sungmin Cha, Youngjoon Yoo +3
Image-mixing augmentations (e.g., Mixup and CutMix), which typically involve mixing two images, have become the de-facto training techniques for image classification. Despite their…
BiHPF: Bilateral High-Pass Filters for Robust Deepfake Detection
Yonghyun Jeong, Doyeon Kim, Seungjai Min +3
The advancement in numerous generative models has a two-fold effect: a simple and easy generation of realistic synthesized images, but also an increased risk of malicious abuse of…