AI Researcher at UNIST AIGS

Junsu Kim

Continual Learning Open-world Detection Vision-Language + Diffusion

Current Base UNIST Busan Centum Campus

Seeking AI Research Internships 2D/3D, continual learning, vision-language, and diffusion systems.

I am a Combined MS/PhD student at UNIST AIGS, advised by Prof. Seungryul Baek. My work focuses on continual learning, open-world detection, and vision-language systems.

Previously, I interned at NAVER AI Lab advised by Dongyoon Han, where I studied backbone architectures and analyzed internal representations of large-scale models. I also serve as an NVIDIA AI Ambassador, with a strong interest in applied AI for everyday problems.

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CVPR 2024 Highlight Poster

Presenting diffusion-based replay research for class-incremental object detection.

click to denoise

Recent Highlights

2026 1st Place in the CVPPA@ECCV'26 BuzzSpot Challenge (Solo Entry · Small Object Detection) Code

2025 Outstanding Reviewer at BMVC 2025

2025 Jul 2025 · One paper accepted to BMVC (co-first author)

2025 Jul 2025 · Two papers accepted to ICCV Workshops (1st author)

Highlight CVPR 2024 first-author paper selected as Highlight Poster (top 2.8%)

Open to Opportunities

Looking for research internships in industry. Message me

Interested in practical research around 2D/3D representation, continual learning, and large-scale vision-language or diffusion models.

Publications

0+ Total Citations

BMVC 2025

B-RIGHT: Benchmark Re-evaluation for Integrity in Generalized Human-Object Interaction Testing

J. Kim*, Y. Jang*, H. Kim, E. Lee, E. Kim, S. Baek, J. Yoo

Paper

ICCV-W 2025 3 citations

Can Synthetic Images Conquer Forgetting? Beyond Unexplored Doubts in Few-Shot Class-Incremental Learning

J. Kim, Y. Ku, S. Baek

Paper

ICCV-W 2025

Revisiting Reliability in the Reasoning-based Pose Estimation Benchmark

J. Kim, N. Kim, J. Lee, I. Park, D. Han, S. Baek

Paper Code & Data

ArXiv 2025 1 citation

Beyond Synthetic Replays: Turning Diffusion Features into Few-Shot Class-Incremental Learning Knowledge

J. Kim, Y. Ku, D. Han, S. Baek

Paper

CVPR Highlight · Top 2.8%

CVPR 2024 · Highlight 92 citations

SDDGR: Stable Diffusion-based Deep Generative Replay for Class Incremental Object Detection

J. Kim, H. Cho, J. Kim, Y. Tiruneh, S. Baek

Paper

CVPR-W 2024 51 citations

VLM-PL: Advanced Pseudo Labeling Approach for Class Incremental Object Detection with Vision-Language Model

J. Kim, Y. Ku, J. Kim, J. Cha, S. Baek

Paper

ICASSP 2024 4 citations

Class-Wise Buffer Management for Incremental Object Detection: An Effective Buffer Training Strategy

J. Kim, S. Hong, C. Kim, J. Kim, Y. Tiruneh, J. On, J. Song, S. Choi, S. Baek

Paper

IEIE Summer 2023

Reducing Data Imbalance for Object Detection

J. Kim, S. Hong, C. Kim, J. Kim, J. On, Y. Tiruneh, J. Song, S. Choi, S. Baek

JKAIA 2022

Temporal MANO-Based Video Hand Pose and Shape Estimation

H. Park, J. Kim, J. Kim, S. Baek

 Best Paper Award

                    IEIE Fall 2021
                
Multi-Task Learning Approach to Autonomous Driving Techniques
I. Lee, J. Kim, H. Lee, Y. Kim, D. Lee, H. Lee

 Best Paper Award

                    KICS Summer 2021
                
Deep Learning-Based Self-Driving Systems for Swarm Vehicles
H. Kim, J. Kim, I. Lee, H. Lee

 Best Paper Award

                    IEMEK ICT 2021
                
AI Edge Server Design for Swarm Vehicular Networks
J. Kim, H. Kim, I. Lee, H. Lee

KICS Winter 2021

AI-Enabled Low-Complexity Autonomous Driving Using TensorRT

H. Kim, J. Kim, I. Lee, H. Lee