Seokeon Choi

I am a Staff Research Engineer in the Personalization of generative AI and On-device learning team at Qualcomm AI Research. Before joining Qualcomm, I completed my Ph.D. in Electrical Engineering at KAIST, advised by Prof. Changick Kim. During my Ph.D., I was a Research Intern in the TensorFlow Model Optimization team at Google, and a Visiting Researcher at CMU under the guidance of Prof. Alex Hauptmann


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Email: bismex (at) gmail.com / seokchoi (at) qti.qualcomm.com

Research Experiences

Education

News

Research Interest

My research interests lie in computer vision and machine learning. The purpose of my research is to bridge the gap between cutting-edge machine learning studies and real-world problems, thereby providing practical solutions. With this goal in mind, my current research focuses on (1) Generative AI for Vision, (2) Transferability and Generalizability, (3) Machine Perception, (4) Human Understanding, (5) On-device Learning, and (6) 3D vision.

In particular, I am actively researching Personalized Text-to-Image Diffusion Models, Text guided Video Editing, and Vision-Language Models (VLM).


Selected publications by topics

Research Timeline

Selected Publications

Progressive Random Convolutions for Single Domain Generalization


Seokeon Choi, Debasmit Das, Sungha Choi, Seunghan Yang, Hyunsin Park, Sungrack Yun

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

[paper] [supp] [video] [slide] [poster

Neural Transformation Network to Generate Diverse Views for Contrastive Learning


Taekyung Kim, Debasmit Das, Seokeon Choi, Minki Jeong, Seunghan Yang, Sungrack Yun, Changick Kim

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

[paper] [supp] [poster

Improving Test-Time Adaptation via Shift-agnostic Weight Regularization and Nearest Source Prototypes


Sungha Choi, Seunghan Yang, Seokeon Choi, Sungrack Yun

European Conference on Computer Vision (ECCV), 2022

[paper]

Learning to Discriminate Information for Online Action Detection: Analysis and Application


Sumin Lee, Hyunjun Eun, Jinyoung Moon, Seokeon Choi, Yoonhyung Kim, Chanho Jung, Changick Kim

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022

[paper] [code]

Just a Few Points are All You Need for Multi-view Stereo: A Novel Semi-supervised Learning Method for Multi-view Stereo


Taekyung Kim, Jaehoon Choi, Seokeon Choi, Dongki Jung, Changick Kim

IEEE/CVF International Conference on Computer Vision (ICCV), 2021

[paper] [supp]

Meta Batch-Instance Normalization for Generalizable Person Re-Identification


Seokeon Choi, Taekyung Kim, Minki Jeong, Hyoungseob Park, Changick Kim

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021

[paper] [supp] [code

Few-shot Open-set Recognition by Transformation Consistency


Minki Jeong, Seokeon Choi, Changick Kim

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021

[paper] [supp] [code]

MobileHumanPose: Toward Real-time 3D Human Pose Estimation in Mobile Devices


Sangbum Choi, Seokeon Choi, Changick Kim

IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshop (CVPRW), 2021

[paper] [code

Robust Long-Term Object Tracking via Improved Discriminative Model Prediction


Seokeon Choi, Junhyun Lee, Yunsung Lee, Alex Hauptmann

European Conference on Computer Vision Workshop (ECCVW), 2020

[paper] [code] [video(1min, ENG)] [video(12min, ENG)]

Hi-CMD: Hierarchical Cross-Modality Disentanglement for Visible-Infrared Person Re-Identification


Seokeon Choi, Sumin Lee, Youngeun Kim, Taekyung Kim, Changick Kim

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020

[paper] [supp] [code] [video(1min, ENG)] [video(5min, KOR)] [poster] [slide(short)] [slide(long)]

RPM-Net: Robust Pixel-Level Matching Networks for Self-Supervised Video Object Segmentation


Youngeun Kim, Seokeon Choi, Hankyeol Lee, Taekyung Kim, Changick Kim

IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2020

[paper] [supp] [video(oral presentation)]

Bilinear Siamese Networks with Background Suppression for Visual Object Tracking


Hankyeol Lee, Seokeon Choi, Youngeun Kim, Changick Kim

British Machine Vision Conference (BMVC), 2019 (Spotlight)

[paper]

Diversify and Match: A Domain Adaptive Representation Learning Paradigm for Object Detection


Taekyung Kim, Minki Jeong, Seunghyeon Kim, Seokeon Choi, Changick Kim

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019

[paper] [supp] [code]

Skeleton-based Gait Recognition via Robust Frame-level Matching


Seokeon Choi, Jonghee Kim, Wonjun Kim, Changick Kim

IEEE Transactions on Information Forensics and Security (TIFS), 2019

[paper] [code] [dataset]

A Memory Model based on the Siamese Network for Long-term Tracking


*Hankyeol Lee, *Seokeon Choi, Changick Kim (*Equal contribution)

European Conference on Computer Vision Workshop (ECCVW), 2018

[paper] [code]

US patents


Awards, Honors, and Scholarship


Professional Activities


Reviewer of International Conferences 


Reviewer of International Journals 


Teaching Assistant 


Invited Talks