14 citations · 15 across the 6 of their papers we have counts for
6 papers
AlphaFace: High Fidelity and Real-time Face Swapper Robust to Facial Pose
Jongmin Yu, Hyeontaek Oh, Zhongtian Sun +3
Existing face-swapping methods often deliver competitive results in constrained settings but exhibit substantial quality degradation when handling extreme facial poses. To improve…
Adversarial Denoising Diffusion Model for Unsupervised Anomaly Detection
Jongmin Yu, Hyeontaek Oh, Jinhong Yang
In this paper, we propose the Adversarial Denoising Diffusion Model (ADDM). The ADDM is based on the Denoising Diffusion Probabilistic Model (DDPM) but complementarily trained by a…
Normality-Calibrated Autoencoder for Unsupervised Anomaly Detection on Data Contamination
Jongmin Yu, Hyeontaek Oh, Minkyung Kim +1
In this paper, we propose Normality-Calibrated Autoencoder (NCAE), which can boost anomaly detection performance on the contaminated datasets without any prior information or expli…
Camera-Tracklet-Aware Contrastive Learning for Unsupervised Vehicle Re-Identification
Jongmin Yu, Junsik Kim, Minkyung Kim +1
Recently, vehicle re-identification methods based on deep learning constitute remarkable achievement. However, this achievement requires large-scale and well-annotated datasets. In…
Unsupervised Person Re-identification via Multi-Label Prediction and Classification based on Graph-Structural Insight
Jongmin Yu, Hyeontaek Oh
This paper addresses unsupervised person re-identification (Re-ID) using multi-label prediction and classification based on graph-structural insight. Our method extracts features f…
Unsupervised Vehicle Re-Identification via Self-supervised Metric Learning using Feature Dictionary
Jongmin Yu, Hyeontaek Oh
The key challenge of unsupervised vehicle re-identification (Re-ID) is learning discriminative features from unlabelled vehicle images. Numerous methods using domain adaptation hav…