Perceptual Artificial Intelligence LAB
About us π
"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.Β
We are actively involved in advancing state-of-the-art AI technologies, encompassing intelligent surveillance systems, content generation systems, autonomous driving, and more.
We are open π«
We are waiting for self-motivated and enthusiastic researchers to join our team. Contact us using the provided link.
News π¬
[24.09.30] Prof. Eom gave a presentation on 'Robust Person Re-Identification and Its Applications in TV Broadcasting' at LG Electronics π’
[24.09.04] A paper about 'Attribute-based Person Re-identification' has been accepted to ESWA (SCI Top 7%, Impact Factor = 7.5) π₯
[24.09.02] Juhyun Park joined our lab! Welcome πΏ
[24.08.26] Prof. Eom gave a presentation on 'Person Re-identification' at KAIST Computer Vision LAB π’
[24.08.06] Prof. Eom gave a presentation on 'Representation Learning for Robust Person Re-identification' at SKTelecom's Computer Vision R&D π’
[24.06.25] Prof. Eom gave a presentation during the Young Researcher session at the Korean Institute of Broadcast and Media π’
[24.03.04] Dahyeon Gye, Giyeol Kim, Changhyun Roh, Jeahun Sung and Hyunseo Lee joined our lab! Welcome πΏ
[23.11.20] Prof. Eom gave a presentation on 'Development of Vision-Based AI Technology for Active Robots' at the Chung-Ang University Medical Convergence Research Symposium π’
[23.10.25] Prof. Eom gave a presentation on 'Development Status and Industrial Applications of AI-Based Computer Vision Tech' at Hyundai Motor's E-Forest Tech DayΒ π’
[23.09.21] Prof. Eom gave a presentation in the "Special Topics in Software Technology" Course at Gachon University π’
[23.09.01] Perceptual AI LAB is newly opened
Research Area π§π»βπ¬
πΈ Intelligent Surveillance SystemΒ
Person Re-Identification
Face Recognition
Anomaly Detection
π¨ Generative Model
Image/Video Generation
Attribute Manipulation
Deep Fake Detection
π οΈ Efficient Model
Model Quantization
Neural Architecture Search
π€ Multi-modal Machine Perception
VisionΒ + Natural Language (+ Other modalities)
Detection/Segmentation