33 citations · 71 across the 10 of their papers we have counts for
5 papers
Improving Weakly-Supervised Object Localization Using Adversarial Erasing and Pseudo Label
Byeongkeun Kang, Sinhae Cha, Yeejin Lee
Weakly-supervised learning approaches have gained significant attention due to their ability to reduce the effort required for human annotations in training neural networks. This p…
Enhancing Long-Term Person Re-Identification Using Global, Local Body Part, and Head Streams
Duy Tran Thanh, Yeejin Lee, Byeongkeun Kang
This work addresses the task of long-term person re-identification. Typically, person re-identification assumes that people do not change their clothes, which limits its applicatio…
Pixel-Level Clustering Network for Unsupervised Image Segmentation
Cuong Manh Hoang, Byeongkeun Kang
While image segmentation is crucial in various computer vision applications, such as autonomous driving, grasping, and robot navigation, annotating all objects at the pixel-level f…
FDCNet: Feature Drift Compensation Network for Class-Incremental Weakly Supervised Object Localization
Sejin Park, Taehyung Lee, Yeejin Lee +1
This work addresses the task of class-incremental weakly supervised object localization (CI-WSOL). The goal is to incrementally learn object localization for novel classes using on…
Sampling Agnostic Feature Representation for Long-Term Person Re-identification
Seongyeop Yang, Byeongkeun Kang, Yeejin Lee
Person re-identification is a problem of identifying individuals across non-overlapping cameras. Although remarkable progress has been made in the re-identification problem, it is…