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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 recent research focuses on generative models, captivated by their positive impact on the AI community. Currently, I'm focused on enhancing diffusion models' generalization and adaptabtiliy, so they can function effectively as strong vision foundation models. **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 |