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 |