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Vision & Learning Laboratory
Current Research
About Research
Welcome to the Vision and Learning laboratory at Inha University.
Vision and Learning laboratory mainly focuses on cutting-edge computer vision and machine learning technology for object perception, visual understanding, and scene analysis. In particular, we mainly focus on developing algorithms for object tracking, detection, image forensic and recognition from images and videos which can be applied for CCTV, cameras, and mobile devices.
NOTICE: We are looking for highly motivated undergraduate, M.S., and Ph.D. students.
(컴퓨터 비전, 머신 러닝, 딥러닝에 관심 있는 학사, 석사, 박사 연구원을 모집합니다. 관심있는 분은 연락 바랍니다.)

Latest Publications

Improving Data-Free Quantization with Confidence-Guided Data Synthesis

ICT Express April 2026
Deok-Woong Kim, and Seung-Hwan Bae*

MVLM: Template-Free Tracking via Vision–Language Margin Confidence and Memory-Gated Tracking

CVPR (Top-tier) June 2026
Dae-Hyeon Park, Mina Baek, Jeong-Hun Ha, Chan-Seop Park, Jamshidjon Ganiev, and Seung-Hwan Bae*

Gated Side Adapters with Memory-efficient Fine Tuning for RGB-T Tracking

ICT Express Vol. 12, pp. 523-529 April 2026
Dae-Hyeon Park, Mina Baek, and Seung-Hwan Bae*

Neural-NGBoost: Natural Gradient Boosting with Neural Network Base Learners

ICT Express Vol. 11, pp. 974-980 October 2025
Jamshidjon Ganiev, Deok-Woong Kim, and Seung-Hwan Bae*

A New Multi-Source Light Detection Benchmark and Semi-Supervised Focal Light Detection

NeurIPS (Top-tier) Vol. 38, pp. 1-14 December 2024
Jae-Yong Baek, Yong-Sang Yoo, and Seung-Hwan Bae*