ContraGAN: Contrastive Learning for Conditional Image Generation. - Minguk Kang; Jaesik Park (NeurIPS, 2020)

Contrastive Generative Adversarial Networks. - Minguk Kang; Jaesik Park (CoRR, 2020)

Rebooting ACGAN: Auxiliary Classifier GANs with Stable Training. - Minguk Kang; Woohyeon Shim; Minsu Cho; Jaesik Park (NeurIPS, 2021)

Context-Aware Image Completion. - Jinoh Cho; Minguk Kang; Vibhav Vineet; Jaesik Park (CoRR, 2022)

Scaling up GANs for Text-to-Image Synthesis. - Minguk Kang; Jun-Yan Zhu; Richard Zhang 001; Jaesik Park; Eli Shechtman; Sylvain Paris; Taesung Park (CVPR, 2023)

Holistic Evaluation of Text-to-Image Models. - Tony Lee; Michihiro Yasunaga; Chenlin Meng; Yifan Mai 001; Joon Sung Park; Agrim Gupta; Yunzhi Zhang; Deepak Narayanan; Hannah Teufel; Marco Bellagente; Minguk Kang; Taesung Park; et al. (NeurIPS, 2023)

Fill-Up: Balancing Long-Tailed Data with Generative Models. - Joonghyuk Shin; Minguk Kang; Jaesik Park (CoRR, 2023)

RISCLIP: Referring Image Segmentation Framework using CLIP. - Seoyeon Kim; Minguk Kang; Jaesik Park (CoRR, 2023)

StudioGAN: A Taxonomy and Benchmark of GANs for Image Synthesis. - Minguk Kang; Joonghyuk Shin; Jaesik Park (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Distilling Diffusion Models Into Conditional GANs. - Minguk Kang; Richard Zhang 001; Connelly Barnes; Sylvain Paris; Suha Kwak; Jaesik Park; Eli Shechtman; Jun-Yan Zhu; Taesung Park (ECCV (28), 2024)

Extending CLIP's Image-Text Alignment to Referring Image Segmentation. - Seoyeon Kim; Minguk Kang; Dongwon Kim; Jaesik Park; Suha Kwak (NAACL-HLT, 2024)