activity
20172021
most citedDynamics Transfer GAN: Generating Video by Transferring Arbitrary Temporal Dynamics from a Source Video to a Single Target Image

15 citations · 15 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV2021

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…

cs.CV2021

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…

cs.CV2021

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…

cs.CV2020

Comprehensive Facial Expression Synthesis using Human-Interpretable Language

Joanna Hong, Jung Uk Kim, Sangmin Lee +1

Recent advances in facial expression synthesis have shown promising results using diverse expression representations including facial action units. Facial action units for an elabo…

cs.CV2018

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…

cs.CV201715 cited

Dynamics Transfer GAN: Generating Video by Transferring Arbitrary Temporal Dynamics from a Source Video to a Single Target Image

Wissam J. Baddar, Geonmo Gu, Sangmin Lee +1

In this paper, we propose Dynamics Transfer GAN; a new method for generating video sequences based on generative adversarial learning. The spatial constructs of a generated video s…