activity
20192022
most citedExploring Patch-wise Semantic Relation for Contrastive Learning in Image-to-Image Translation Tasks

7 citations · 9 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV20227 cited

Exploring Patch-wise Semantic Relation for Contrastive Learning in Image-to-Image Translation Tasks

Chanyong Jung, Gihyun Kwon, Jong Chul Ye

Recently, contrastive learning-based image translation methods have been proposed, which contrasts different spatial locations to enhance the spatial correspondence. However, the m…

cs.CV2021

Diagonal Attention and Style-based GAN for Content-Style Disentanglement in Image Generation and Translation

Gihyun Kwon, Jong Chul Ye

One of the important research topics in image generative models is to disentangle the spatial contents and styles for their separate control. Although StyleGAN can generate content…

cs.CV2019

Progressive Face Super-Resolution via Attention to Facial Landmark

Deokyun Kim, Minseon Kim, Gihyun Kwon +1

Face Super-Resolution (SR) is a subfield of the SR domain that specifically targets the reconstruction of face images. The main challenge of face SR is to restore essential facial…

eess.IV2019

Generation of 3D Brain MRI Using Auto-Encoding Generative Adversarial Networks

Gihyun Kwon, Chihye Han, Dae-shik Kim

As deep learning is showing unprecedented success in medical image analysis tasks, the lack of sufficient medical data is emerging as a critical problem. While recent attempts to s…

q-bio.NC20192 cited

Representation of White- and Black-Box Adversarial Examples in Deep Neural Networks and Humans: A Functional Magnetic Resonance Imaging Study

Chihye Han, Wonjun Yoon, Gihyun Kwon +2

The recent success of brain-inspired deep neural networks (DNNs) in solving complex, high-level visual tasks has led to rising expectations for their potential to match the human v…