125 citations · 340 across the 34 of their papers we have counts for
8 papers · 1 filter
Drivers Drowsiness Detection using Condition-Adaptive Representation Learning Framework
Jongmin Yu, Sangwoo Park, Sangwook Lee +1
We propose a condition-adaptive representation learning framework for the driver drowsiness detection based on 3D-deep convolutional neural network. The proposed framework consists…
Unconstrained Road Marking Recognition with Generative Adversarial Networks
Younkwan Lee, Juhyun Lee, Yoojin Hong +2
Recent road marking recognition has achieved great success in the past few years along with the rapid development of deep learning. Although considerable advances have been made, t…
Practical License Plate Recognition in Unconstrained Surveillance Systems with Adversarial Super-Resolution
Younkwan Lee, Jiwon Jun, Yoojin Hong +1
Although most current license plate (LP) recognition applications have been significantly advanced, they are still limited to ideal environments where training data are carefully a…
SNIDER: Single Noisy Image Denoising and Rectification for Improving License Plate Recognition
Younkwan Lee, Juhyun Lee, Hoyeon Ahn +1
In this paper, we present an algorithm for real-world license plate recognition (LPR) from a low-quality image. Our method is built upon a framework that includes denoising and rec…
Boosting Network Weight Separability via Feed-Backward Reconstruction
Jongmin Yu, Hyeontaek Oh
This paper proposes a new evaluation metric and boosting method for weight separability in neural network design. In contrast to general visual recognition methods designed to enco…
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,…