2 citations · 4 across the 6 of their papers we have counts for
6 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…
Tackling Background Distraction in Video Object Segmentation
Suhwan Cho, Heansung Lee, Minhyeok Lee +4
Semi-supervised video object segmentation (VOS) aims to densely track certain designated objects in videos. One of the main challenges in this task is the existence of background d…
Pixel-Level Bijective Matching for Video Object Segmentation
Suhwan Cho, Heansung Lee, Minjung Kim +2
Semi-supervised video object segmentation (VOS) aims to track the designated objects present in the initial frame of a video at the pixel level. To fully exploit the appearance inf…
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…
PMVOS: Pixel-Level Matching-Based Video Object Segmentation
Suhwan Cho, Heansung Lee, Sungmin Woo +2
Semi-supervised video object segmentation (VOS) aims to segment arbitrary target objects in video when the ground truth segmentation mask of the initial frame is provided. Due to t…
CRVOS: Clue Refining Network for Video Object Segmentation
Suhwan Cho, MyeongAh Cho, Tae-young Chung +2
The encoder-decoder based methods for semi-supervised video object segmentation (Semi-VOS) have received extensive attention due to their superior performances. However, most of th…