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"Through the lens of computer and the ingenuity of artificial intelligence, we strive to aid humanity and enhance our lives."
Welcome! Our team explores ways to enable machines to imitate the capabilities of the human visual system, allowing them to perceive the world in a human manner.
We are actively involved in advancing state-of-the-art AI technologies, encompassing intelligent surveillance systems, content generation systems, autonomous driving, and more.
News 📬
News 📬
[25.03.04]
Sukhun Ko, Weeyoung Kwon and Gyuwon Han joined our lab! Welcome.
[25.02.27]
Two paper have been accepted to CVPR 2025. Congrats to all the authors :)
(CV Top-tier Conference, h5-index = 440) 🔥
[25.02.13]
Prof. Eom was recognized as an Excellent Instructor for the 2024 Fall semester based on course evaluations for the 'Artificial Intelligence' lecture.
[25.02.07]
Prof. Eom gave a presentation during the Young Researcher session on Image Processing and Image Understanding (IPIU) 2025.
[24.11.28]
Prof. Eom gave a presentation on 'Toward Robust Person Re-Identification Advances in Representation Learning' during a seminar lecture at Yonsei University.
[24.10.18]
Prof. Eom gave a presentation during the Young Researcher session on IEIE Conference on AI Signal Processing.
[24.09.30]
Prof. Eom gave a presentation on 'Robust Person Re-Identification and Its Applications in TV Broadcasting' at LG Electronics.
[24.09.04]
A paper about 'Attribute-based Person Re-identification' has been accepted to ESWA
(SCI Top 7%, Impact Factor = 7.5) 🔥
[24.09.02]
Juhyun Park joined our lab. Welcome!
[24.08.26]
Prof. Eom gave a presentation on 'Person Re-identification' at KAIST Computer Vision LAB.
Research Area 🧑🏻🔬
Research Area 🧑🏻🔬
📸 Intelligent Surveillance System
Person Re-Identification
Face Recognition
Anomaly Detection
🎨 Generative Model
Image/Video Generation
Attribute Manipulation
Deep Fake Detection
🛠️ Efficient Model
Model Quantization
Neural Architecture Search
🤖 Multi-modal Machine Perception
Vision + Natural Language (+ Other modalities)
Detection/Segmentation
We are open 💫
We are open 💫
We are always waiting for self-motivated and enthusiastic researchers to join our team. Contact us using the provided link.
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