I am a research scientist at NAVER AI Lab, working on computer vision and machine learning. My research interests have been on learning models without human supervision (unsupervised learning) and developing machines that can realize our visual imagination (generative modeling). I received B.S. and M.S. in Computer Science, both at Korea University. During my Master’s program, I was advised by Prof. Jaegul Choo.

Publications

Generator Knows What Discriminator Should Learn in Unconditional GANs
Gayoung Lee, Hyunsu Kim, Junho Kim, Seonghyeon Kim, Jung-Woo Ha, Yunjey Choi
ECCV 2022
Paper | Code
Feature Statistics Mixing Regularization for Generative Adversarial Networks
Junho Kim, Yunjey Choi, Youngjung Uh
CVPR 2022
Paper | Code
Rethinking the Truly Unsupervised Image-to-Image Translation
Kyungjune Baek, Yunjey Choi, Youngjung Uh, Jaejun Yoo, Hyunjung Shim
ICCV 2021
Paper | Code
StyleMapGAN: Exploiting Spatial Dimensions of Latent in GAN for Real-time Image Editing
Hyunsu Kim, Yunjey Choi, Junho Kim, Sungjoo Yoo, Youngjung Uh
CVPR 2021
Paper | Code | Video
Reliable Fidelity and Diversity Metrics for Generative Models
Muhammad Ferjad Naeem*, Seong Joon Oh*, Youngjung Uh, Yunjey Choi, Jaejun Yoo
ICML 2020 (* indicates equal contribution)
Paper | Code
StarGAN v2: Diverse Image Synthesis for Multiple Domains
Yunjey Choi*, Youngjung Uh*, Jaejun Yoo*, Jung-Woo Ha
CVPR 2020 (* indicates equal contribution)
Paper | Code | Video
StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
Yunjey Choi, Minje Choi, Munyoung Kim, Jung-Woo Ha, Sunghun Kim, Jaegul Choo
CVPR 2018 (Oral presentation)
Paper | Code | Video | Presentation