14 citations · 15 across the 4 of their papers we have counts for
4 papers
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…