Minguk Kang

I am a 4th year Ph.D. student in Graduate School of AI at POSTECH, where I am a member of the Computer Vision Lab under the supervision of Prof. Suha Kwak. I received B.S. in Engineering at Pusan National University.

I focus on computer vision, particularly on the subject of generative modeling and how it can be applied. I am fascinated by the diverse range of vision-related tasks that Generative Adversarial Networks (GANs) can potentially assist with. If you would like to know more about the research projects that I am working on, do not hesitate to reach out to me.

Email: mingukkang1994@gmail.com, mgkang@postech.ac.kr

Education

Feb, 2020 - Present	Pohang University of Science and Technology (POSTECH), Pohang, South Korea Integrated M.S./Ph.D. student in Graduate School of AI
Mar, 2013 - Aug, 2019	Pusan National University, Pusan, South Korea B.S. in Engineering (Major: Mechanical Engineering and Minor: Statistics)

Experience

Jun, 2024 - Sep, 2024	Pika, Palo Alto, United States of America Tech Intern Working with: Chenlin Meng
Jul, 2022 - May, 2024	Adobe Research Creative Intelligence Lab, Remote work at Korea & Onsite work at San Francisco Research Intern Working with: Taesung Park, Connelly Barnes, Eli Shechtman, Jun-Yan Zhu, Richard Zhang, Sylvain Paris
Feb, 2020 - Present	Computer Vision Lab, POSTECH, Pohang, South Korea Integrated M.S./Ph.D. student Supervisor: Prof. Suha Kwak
Aug, 2017 - Jan, 2020	Vision and Intelligent System Lab, Pusan National University, Pusan, South Korea Undergraduate Research Student Supervisor: Prof. Dongjoong Kang

Softwares

Firefly is a text-to-image generative model developed by Adobe and integrated into Photoshop. My research contributed to the development of Firefly.

StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks for image generation. I am the primary inventor of the StudioGAN library.

Publications

Fill-Up: Balancing Long-Tailed Data with Generative Models

Joonghyuk Shin, Minguk Kang, and Jaesik Park

arXiv preprint arXiv:2306.07200 2023

Paper Website
Extending CLIP’s Image-Text Alignment to Referring Image Segmentation

Seoyeon Kim, Minguk Kang, Dongwon Kim, Jaesik Park, and Suha Kwak

Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2024

Paper Code
StudioGAN: A Taxonomy and Benchmark of GANs for Image Synthesis

Minguk Kang, Joonghyuk Shin, and Jaesik Park

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2023

Paper Code
Holistic Evaluation of Text-to-Image Models

Tony Lee, Michihiro Yasunaga, Chenlin Meng, Yifan Mai, Joon Sung Park, Agrim Gupta, Yunzhi Zhang, Deepak Narayanan, Hannah Benita Teufel, Marco Bellagente, Minguk Kang, Taesung Park, Jure Leskovec, Jun-Yan Zhu, Li Fei-Fei, Jiajun Wu, Stefano Ermon, and Percy Liang

Advances in Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track, Spotlight 2023

Paper Website
Scaling up GANs for Text-to-Image Synthesis

Minguk Kang, Jun-Yan Zhu, Richard Zhang, Jaesik Park, Eli Shechtman, Sylvain Paris, and Taesung Park

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Highlight, 2023

Paper Website
Context-Aware Image Completion

Jinoh Cho, Minguk Kang, Vibhav Vineet, and Jaesik Park

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshop, 2023

Paper
Rebooting ACGAN: Auxiliary Classifier GANs with Stable Training

Minguk Kang, Woohyeon Shim, Minsu Cho, and Jaesik Park

Advances in Neural Information Processing Systems (NeurIPS), 2021

Paper Code
ContraGAN: Contrastive Learning for Conditional Image Generation

Minguk Kang, and Jaesik Park

Advances in Neural Information Processing Systems (NeurIPS), 2020

Paper Code