22 citations · 110 across the 22 of their papers we have counts for
6 papers · 1 filter
Mode Variational LSTM Robust to Unseen Modes of Variation: Application to Facial Expression Recognition
Wissam J. Baddar, Yong Man Ro
Spatio-temporal feature encoding is essential for encoding the dynamics in video sequences. Recurrent neural networks, particularly long short-term memory (LSTM) units, have been p…
Feature2Mass: Visual Feature Processing in Latent Space for Realistic Labeled Mass Generation
Jae-Hyeok Lee, Seong Tae Kim, Hakmin Lee +1
This paper deals with a method for generating realistic labeled masses. Recently, there have been many attempts to apply deep learning to various bio-image computing fields includi…
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…