41 citations · 72 across the 10 of their papers we have counts for
10 papers
Bag of Tricks for Domain Adaptive Multi-Object Tracking
Minseok Seo, Jeongwon Ryu, Kwangjin Yoon
In this paper, SIA_Track is presented which is developed by a research team from SI Analytics. The proposed method was built from pre-existing detector and tracker under the tracki…
Learning Multiple Probabilistic Degradation Generators for Unsupervised Real World Image Super Resolution
Sangyun Lee, Sewoong Ahn, Kwangjin Yoon
Unsupervised real world super resolution (USR) aims to restore high-resolution (HR) images given low-resolution (LR) inputs, and its difficulty stems from the absence of paired dat…
An End-to-End Trainable Video Panoptic Segmentation Method usingTransformers
Jeongwon Ryu, Kwangjin Yoon
In this paper, we present an algorithm to tackle a video panoptic segmentation problem, a newly emerging area of research. The video panoptic segmentation is a task that unifies th…
Simple and Efficient Unpaired Real-world Super-Resolution using Image Statistics
Kwangjin Yoon
Learning super-resolution (SR) network without the paired low resolution (LR) and high resolution (HR) image is difficult because direct supervision through the corresponding HR co…
Online Multi-Object Tracking and Segmentation with GMPHD Filter and Mask-based Affinity Fusion
Young-min Song, Young-chul Yoon, Kwangjin Yoon +3
In this paper, we propose a highly practical fully online multi-object tracking and segmentation (MOTS) method that uses instance segmentation results as an input. The proposed met…
NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results
Kai Zhang, Shuhang Gu, Radu Timofte +60
This paper reviews the NTIRE 2020 challenge on perceptual extreme super-resolution with focus on proposed solutions and results. The challenge task was to super-resolve an input im…
Online Multi-Object Tracking Framework with the GMPHD Filter and Occlusion Group Management
Young-min Song, Kwangjin Yoon, Young-Chul Yoon +2
In this paper, we propose an efficient online multi-object tracking framework based on the GMPHD filter and occlusion group management scheme where the GMPHD filter utilizes hierar…
Online Multiple Pedestrians Tracking using Deep Temporal Appearance Matching Association
Young-Chul Yoon, Du Yong Kim, Young-min Song +2
In online multi-target tracking, modeling of appearance and geometric similarities between pedestrians visual scenes is of great importance. The higher dimension of inherent inform…
Multiple Hypothesis Tracking Algorithm for Multi-Target Multi-Camera Tracking with Disjoint Views
Kwangjin Yoon, Young-min Song, Moongu Jeon
In this study, a multiple hypothesis tracking (MHT) algorithm for multi-target multi-camera tracking (MCT) with disjoint views is proposed. Our method forms track-hypothesis trees,…
Online Multi-Object Tracking with Historical Appearance Matching and Scene Adaptive Detection Filtering
Young-chul Yoon, Abhijeet Boragule, Young-min Song +2
In this paper, we propose the methods to handle temporal errors during multi-object tracking. Temporal error occurs when objects are occluded or noisy detections appear near the ob…