no code implementations • 9 Dec 2022 • Minjung Kim, MyeongAh Cho, Heansung Lee, Suhwan Cho, Sangyoun Lee
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 crowded scenes.
1 code implementation • 14 Jul 2022 • Suhwan Cho, Heansung Lee, Minhyeok Lee, Chaewon Park, Sungjun Jang, Minjung Kim, Sangyoun Lee
Semi-supervised video object segmentation (VOS) aims to densely track certain designated objects in videos.
1 code implementation • 4 Oct 2021 • Suhwan Cho, Heansung Lee, Minjung Kim, Sungjun Jang, Sangyoun Lee
Before finding the best matches for the query frame pixels, the optimal matches for the reference frame pixels are first considered to prevent each reference frame pixel from being overly referenced.
no code implementations • 26 Oct 2020 • Tae-young Chung, Heansung Lee, Myeong Ah Cho, Suhwan Cho, Sangyoun Lee
So in this paper, we propose a novel self-supervised learning method using a lot of short videos which has no human labeling, and improve the tracking performance through the re-identification network trained in the self-supervised manner to solve the lack of training data problem.
no code implementations • 18 Sep 2020 • Suhwan Cho, Heansung Lee, Sungmin Woo, Sungjun Jang, Sangyoun Lee
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.
1 code implementation • 10 Feb 2020 • Suhwan Cho, MyeongAh Cho, Tae-young Chung, Heansung Lee, Sangyoun Lee
The encoder-decoder based methods for semi-supervised video object segmentation (Semi-VOS) have received extensive attention due to their superior performances.
Ranked #60 on Semi-Supervised Video Object Segmentation on DAVIS 2016