Junghoon Seo

Hi, I am the principal researcher of AI Robot Team at PIT IN Corp.. My current main scope at work is directing research projects on computer vision and machine learning for robotics and automation. Besides, I am interested in computer graphics, parallel computing, and intelligent sensing technique. Don’t hesitate to contact me via Email or LinkedIn if you have any business!

Specialties

• Machine Learning, Computer Vision, and Computer Graphics
• Parallel Computing on HPC and General-Purpose Computing on GPU
• Intelligent Sensing Techniques for Human-Computer Interaction

Career

• Dec 2024 - Current, Principal Researcher, AI Robot Team @ PIT IN Corp.
• Sep 2020 - Sep 2024, Technical Leader of Research Center & Co-founder @ SI Analytics
• Jul 2017 - Feb 2020, ML/CV Research Scientist @ Satrec Initiative

Education

• Mar 2023 - Feb 2025, KAIST, Daejeon, South Korea
  • Master’s degree in Graduate School of Culture Technology
  • HCI Tech Lab, supervised by Prof. Sang Ho Yoon
• Mar 2014 - Feb 2021, GIST, Gwangju, South Korea
  • B.S degree, Major in Electrical Engineering and Computer Science

Publications (Google Scholar)

• Guided Super Resolution of Land Surface Temperature Using Multi-Satellite Imageries
  • Sunju Lee, Yeji Choi, Beomkyu Choi, Junghoon Seo, Minki Song, Eunha Sohn, Sewoongg Ahn
  • IEEE TGRS. 2025. Link
• Hausdorff Distance Matching with Adaptive Query Denoising for Rotated Detection Transformer
  • Hakjin Lee, Minki Song, Jamyoung Koo, Junghoon Seo
  • IEEE WACV. 2025. Link
• Posture-Informed Muscular Force Learning for Robust Hand Pressure Estimation
  • Junghoon Seo, Kyungjin Seo, Hanseok Jeong, Sangpil Kim, Sang Ho Yoon
  • NeurIPS. 2024. Link
• A Billion-scale Foundation Model for Remote Sensing Images
  • Keumgang Cha, Junghoon Seo, and Taekyung Lee
  • IEEE J-STARS. 2024. Link
• Self-Pair: Synthesizing Changes from Single Source for Object Change Detection in Remote Sensing Imagery
  • Minseok Seo, Hakjin Lee, Yongjin Jeon, and Junghoon Seo
  • IEEE WACV. 2023. Link
• Geometric Remove-and-Retrain (GOAR): Coordinate-Invariant eXplainable AI Assessment
  • Yonghyun Park, Junghoon Seo, Bomseok Park, Seongsu Lee, and Junghyo Jo
  • NeurIPS Workshop. 2023. Link
• Prototype-oriented Unsupervised Change Detection for Disaster Management
  • Youngtack Oh, Minseok Seo, Kim Doyi, and Junghoon Seo
  • NeurIPS Workshop. 2023. Link
• Semi-Implicit Hybrid Gradient Methods with Application to Adversarial Robustness
  • Beomsu Kim and Junghoon Seo
  • AISTATS. 2022. Link Video
• Quantile Autoencoder with Abnormality Accumulation for Anomaly Detection of Multi-variate Sensor Data
  • Seunghyoung Ryu, Jiyeon Yim, Junghoon Seo, Yonggyun Yu, and Hogeon Seo
  • IEEE Access. 2022. Link
• Contrastive Multiview Coding With Electro-Optics for SAR Semantic Segmentation
  • Keumgang Cha, Junghoon Seo, and Yeji Choi
  • IEEE GRSL. 2021. Link
• Training Domain-invariant Object Detector Faster with Feature Replay and Slow Learner
  • Chaehyeon Lee, Junghoon Seo, and Heechul Jung
  • CVPR Workshop. 2021. Link
• On the Power of Deep but Naive Partial Label Learning
  • Junghoon Seo and Joon Suk Huh
  • IEEE ICASSP. 2021. Link
• NL-LinkNet: Toward Lighter but More Accurate Road Extraction with Non-Local Operations
  • Yooseung Wang, Junghoon Seo, and Taegyun Jeon
  • IEEE GRSL. 2021. Link
• Revisiting Classical Bagging with Modern Transfer Learning for On-the-fly Disaster Damage Detector
  • Junghoon Seo, Seungwon Lee, Beomsu Kim, and Taegyun Jeon
  • NeurIPS Workshop. 2019. Link
• Deep Closed-Form Subspace Clustering
  • Junghoon Seo, Jamyoung Koo, and Taegyun Jeon
  • ICCV Workshop. 2019. Link
• Why are Saliency Maps Noisy? Cause of and Solution to Noisy Saliency Maps
  • Beomsu Kim, Junghoon Seo, Jeongyeol Choe, Jamyoung Koo, Seunghyeon Jeon, and Taegyun Jeon
  • ICCV Workshop. 2019. Link
• Bridging Adversarial Robustness and Gradient Interpretability
  • Beomsu Kim, Junghoon Seo, and Taegyun Jeon
  • ICLR Workshop. 2019. Link
• RBox-CNN: Rotated Bounding Box based CNN for Ship Detection in Remote Sensing Image
  • Jamyoung Koo, Junghoon Seo, Seunghyun Jeon, Jeongyeol Choe, and Taegyun Jeon
  • ACM SIGSPATIAL. 2018. Link
• Noise-adding Methods of Saliency Map as Series of Higher Order Partial Derivative
  • Junghoon Seo, Jeongyeol Choe, Jamyoung Koo, SeungHyun Jeon, Beomsu Kim, and Taegyun Jeon
  • ICML Workshop. 2018. Link
• Domain Adaptive Generation of Aircraft on Satellite Imagery via Simulated and Unsupervised Learning
  • Junghoon Seo, Seunghyun Jeon, and Taegyun Jeon
  • ACML Workshop. 2017. Link
• Multi-task Learning for Fine-grained Visual Classification of Aircraft
  • Seunghyun Jeon, Junghoon Seo and Taegyun Jeon
  • ACML Workshop. 2017.

Working Titles Under Review

• Pressure Estimation for Hand-based Interaction
• Hand-Raycasting with Hand Force
• Off-policy Evaluation from Multiple Logging Policies

Awards

• 2024, my lab’s demo, which included the project I was leading, had been selected as the Popular Choice Winner in CHI 2024.
• 2021, I graduated the college with Best Undergraduate Thesis Award.
• 2020, my team ranked the 5th place in xView2 Challange.
• 2018, my team ranked the 3rd-4th place in CVPR NTIRE Super-resolution Challange.
• 2018, my team ranked the 2nd place in DOTA Challange.
• 2016, my team got the grand prize at KISTI National Supercomputing Competition.
• 2016, I got the Qualcomm-GIST Innovation Award.

Talks

• Query as Representation: A Paradigm Shift in Computer Vision Caused by DETR @ Online. Nov 2022. YouTube (Korean)
• Recent XAI Trends in Deep Learning Era: (Under-)specification and Approaches @ KAERI. Feb 2020.
• Back to the Representation Learning with focusing on Visual Self-supervision @ ETRI. Jul 2019. Presentation (Korean)
• Deep Perceptual Super-resolution: Going Beyond Distortion @ KARI. Jul 2018. Presentation

Review-serving

• IEEE Transactions on Pattern Analysis and Machine Intelligence
• IEEE Transactions on Neural Networks and Learning Systems
• IEEE Geoscience and Remote Sensing Letters
• Several Conferences including NeurIPS, CVPR, AISTATS, BMVC…
• Several Workshops on ICCV, ICLR, CVPR…

Patents

• Method for detecting object, granted, 10-2364882
• Method for detecting on-the-fly disaster damage based on image, granted, 10-2255998
• Method for predicting frame using deep learning, application, 10-2023-0115699
• Method, system, and computing device for generating an alternative image of a satellite or aerial image in which an image of an area of interest is replaced, application, 10-2023-0075347
• Method of training object prediction models using ambiguous labels, application, 10-2022-0000169
• Method for detecting object, application, 10-2021-0168545
• Method to detect object, application, 10-2021-0135451
• Method for data clustering, application, 10-2020-0107206

Note

Due to confidentiality provisions related to the field, I cannot disclose the outline of the project to the public.