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Hyelin Nam I'm a master student at KAIST, supervised by Professor Jong Chul Ye. Before starting my Master's degree, I was supervised by Professor Jaegul Choo.
My goal is to advance generative models to enhance perception. I have contributed to this by leveraging diffusion models to better understand
low-level visual features and align these models with given conditions. **I am actively looking for PhD openings starting in Fall 2025** |
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CFG++: Manifold-constrained Classifier Free Guidance For Diffusion Models
Hyungjin Chung*, Jeongsol Kim*, Geon Yeong Park*, Hyelin Nam*, Jong Chul Ye arXiv, 2024 project page / arXiv / code A simple fix to CFG that enables lower guidance scales, improves sample quality and invertibility. |
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Contrastive Denoising Score for Text-guided Latent Diffusion Image Editing
Hyelin Nam, Gihyun Kwon, Geon Yeong Park, Jong Chul Ye CVPR, 2024 project page / arXiv / code Ensure structural correspondence by leveraging diffusion features during the score distillation process. |
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HairFIT: Pose-invariant Hairstyle Transfer via Flow-based Hair Alignment and Semantic-region-aware Inpainting
Chaeyeon Chung*, Taewoo Kim*, Hyelin Nam*, Seunghwan Choi, Gyojung Gu, Sunghyun Park, Jaegul Choo BMVC, Oral Presentation, 2022 Best Paper Award, Korean Artificial Intelligence Association, 2021 arXiv |