3 citations · 4 across the 7 of their papers we have counts for
9 papers
Occluded Person Re-Identification via Relational Adaptive Feature Correction Learning
Minjung Kim, MyeongAh Cho, Heansung Lee +2
Occluded person re-identification (Re-ID) in images captured by multiple cameras is challenging because the target person is occluded by pedestrians or objects, especially in crowd…
RandomSEMO: Normality Learning Of Moving Objects For Video Anomaly Detection
Chaewon Park, Minhyeok Lee, MyeongAh Cho +1
Recent anomaly detection algorithms have shown powerful performance by adopting frame predicting autoencoders. However, these methods face two challenging circumstances. First, the…
Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss
Chaewon Park, Minhyeok Lee, MyeongAh Cho +1
UNet-based methods have shown outstanding performance in salient object detection (SOD), but are problematic in two aspects. 1) Indiscriminately integrating the encoder feature, wh…
FastAno: Fast Anomaly Detection via Spatio-temporal Patch Transformation
Chaewon Park, MyeongAh Cho, Minhyeok Lee +1
Video anomaly detection has gained significant attention due to the increasing requirements of automatic monitoring for surveillance videos. Especially, the prediction based approa…
A NIR-to-VIS face recognition via part adaptive and relation attention module
Rushuang Xu, MyeongAh Cho, Sangyoun Lee
In the face recognition application scenario, we need to process facial images captured in various conditions, such as at night by near-infrared (NIR) surveillance cameras. The ill…
Multi-object tracking with self-supervised associating network
Tae-young Chung, Heansung Lee, Myeong Ah Cho +2
Multi-Object Tracking (MOT) is the task that has a lot of potential for development, and there are still many problems to be solved. In the traditional tracking by detection paradi…