Seungyong Lee

My research interests lie in computer vision, particularly in both understanding and generating complex visual worlds. I am interested in visual recognition as a way to perceive the world, and in generative models as a means to recreate and manipulate it. I am also passionate about large-scale model training and scalable inference systems from an engineering perspective. At NXN Labs, I have led the development of virtual try-on models and image generation frameworks, taking ownership of the full pipeline—from problem definition and data collection to model design, training, and deployment. I studied Mathematics and Electrical Engineering at KAIST, where I am currently on a leave of absence.

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We introduced a unified and scalable diffusion transformer for jointly learning virtual try-on and try-off, enabling robust garment–target correspondence.

We proposed a unified diffusion transformer that performs both virtual try-on and try-off, achieving state-of-the-art results on both tasks.

We achieve high-fidelity text-driven fashion style editing in a compute-efficient manner by leveraging a generative human prior.

NXN Labs
AI Research Engineer, Founding Member (Jul 2023 – Present)

Led research and engineering initiatives in virtual try-on and virutal human for large-scale applications. Designed scalable data and training pipelines for multi-node GPU clusters. Developed and maintained a k8s inference architecture serving multiple model endpoints. Built a VLM-driven automation pipeline for image–metadata preprocessing and database ingestion, and defined new research directions in depth-aware segmentation and multi-context image editing. Supervised and mentored four engineer interns, fostering collaboration across model, data, and deployment tasks.

Lunit
AI Research Scientist Intern (Jan 2023 – Jul 2023)

Worked on medical image recognition using computer vision techniques, focusing on tumor cell detection and segmentation in pathological images with Vision Transformers.

Koh Young Technology R&D Center
AI Engineer Intern (Aug 2020 – Feb 2021)

Participated in an anomaly detection project for inspecting defects on semiconductor substrates and developed data labeling and real-time inference tools.

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