13 citations · 13 across the 8 of their papers we have counts for
10 papers
Visual Comfort Aware-Reinforcement Learning for Depth Adjustment of Stereoscopic 3D Images
Hak Gu Kim, Minho Park, Sangmin Lee +2
Depth adjustment aims to enhance the visual experience of stereoscopic 3D (S3D) images, which accompanied with improving visual comfort and depth perception. For a human expert, th…
Towards a Better Understanding of VR Sickness: Physical Symptom Prediction for VR Contents
Hak Gu Kim, Sangmin Lee, Seongyeop Kim +2
We address the black-box issue of VR sickness assessment (VRSA) by evaluating the level of physical symptoms of VR sickness. For the VR contents inducing the similar VR sickness le…
Video Prediction Recalling Long-term Motion Context via Memory Alignment Learning
Sangmin Lee, Hak Gu Kim, Dae Hwi Choi +2
Our work addresses long-term motion context issues for predicting future frames. To predict the future precisely, it is required to capture which long-term motion context (e.g., wa…
Generative Guiding Block: Synthesizing Realistic Looking Variants Capable of Even Large Change Demands
Minho Park, Hak Gu Kim, Yong Man Ro
Realistic image synthesis is to generate an image that is perceptually indistinguishable from an actual image. Generating realistic looking images with large variations (e.g., larg…
ICADx: Interpretable computer aided diagnosis of breast masses
Seong Tae Kim, Hakmin Lee, Hak Gu Kim +1
In this study, a novel computer aided diagnosis (CADx) framework is devised to investigate interpretability for classifying breast masses. Recently, a deep learning technology has…
STAN: Spatio-Temporal Adversarial Networks for Abnormal Event Detection
Sangmin Lee, Hak Gu Kim, Yong Man Ro
In this paper, we propose a novel abnormal event detection method with spatio-temporal adversarial networks (STAN). We devise a spatio-temporal generator which synthesizes an inter…
VR IQA NET: Deep Virtual Reality Image Quality Assessment using Adversarial Learning
Heoun-taek Lim, Hak Gu Kim, Yong Man Ro
In this paper, we propose a novel virtual reality image quality assessment (VR IQA) with adversarial learning for omnidirectional images. To take into account the characteristics o…
Measurement of exceptional motion in VR video contents for VR sickness assessment using deep convolutional autoencoder
Hak Gu Kim, Wissam J. Baddar, Heoun-taek Lim +2
This paper proposes a new objective metric of exceptional motion in VR video contents for VR sickness assessment. In VR environment, VR sickness can be caused by several factors wh…
Iterative Deep Convolutional Encoder-Decoder Network for Medical Image Segmentation
Jung Uk Kim, Hak Gu Kim, Yong Man Ro
In this paper, we propose a novel medical image segmentation using iterative deep learning framework. We have combined an iterative learning approach and an encoder-decoder network…
Modality-bridge Transfer Learning for Medical Image Classification
Hak Gu Kim, Yeoreum Choi, Yong Man Ro
This paper presents a new approach of transfer learning-based medical image classification to mitigate insufficient labeled data problem in medical domain. Instead of direct transf…