2 citations · 5 across the 5 of their papers we have counts for
6 papers · 1 filter
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…
Treating Motion as Option to Reduce Motion Dependency in Unsupervised Video Object Segmentation
Suhwan Cho, Minhyeok Lee, Seunghoon Lee +3
Unsupervised video object segmentation (VOS) aims to detect the most salient object in a video sequence at the pixel level. In unsupervised VOS, most state-of-the-art methods lever…
Unsupervised Video Object Segmentation via Prototype Memory Network
Minhyeok Lee, Suhwan Cho, Seunghoon Lee +2
Unsupervised video object segmentation aims to segment a target object in the video without a ground truth mask in the initial frame. This challenging task requires extracting feat…
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…