8 citations · 18 across the 6 of their papers we have counts for
10 papers
Domain-generalizable Face Anti-Spoofing with Patch-based Multi-tasking and Artifact Pattern Conversion
Seungjin Jung, Yonghyun Jeong, Minha Kim +3
Face Anti-Spoofing (FAS) algorithms, designed to secure face recognition systems against spoofing, struggle with limited dataset diversity, impairing their ability to handle unseen…
Beyond Spatial Frequency: Pixel-wise Temporal Frequency-based Deepfake Video Detection
Taehoon Kim, Jongwook Choi, Yonghyun Jeong +4
We introduce a deepfake video detection approach that exploits pixel-wise temporal inconsistencies, which traditional spatial frequency-based detectors often overlook. Traditional…
Group-wise Scaling and Orthogonal Decomposition for Domain-Invariant Feature Extraction in Face Anti-Spoofing
Seungjin Jung, Kanghee Lee, Yonghyun Jeong +3
Domain Generalizable Face Anti-Spoofing (DGFAS) methods effectively capture domain-invariant features by aligning the directions (weights) of local decision boundaries across domai…
FrePGAN: Robust Deepfake Detection Using Frequency-level Perturbations
Yonghyun Jeong, Doyeon Kim, Youngmin Ro +1
Various deepfake detectors have been proposed, but challenges still exist to detect images of unknown categories or GAN models outside of the training settings. Such issues arise f…
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…
FICGAN: Facial Identity Controllable GAN for De-identification
Yonghyun Jeong, Jooyoung Choi, Sungwon Kim +5
In this work, we present Facial Identity Controllable GAN (FICGAN) for not only generating high-quality de-identified face images with ensured privacy protection, but also detailed…