I am a PhD student at Statistical Inference and Information Theory (SIIT), KAIST, supervised by Junmo Kim. Prior to this, I obtained my Master degree (2023) in Electrical Engineering, KAIST, and Bachelor degree (2021) in Engineering, DGIST.
My research interest lies in user-centric content creation, focusing on efficient methods for image synthesis, fine-tuning pre-trained models or guide sampling process to enhance performance, and generating image aligned with user intent.
Email / CV / GitHub / LinkedIn / GoogleScholar
Contact: jiwan.hur [at] kaist.ac.kr
@inproceedings{choi2026prism,
title={PRISM: Video Dataset Condensation with Progressive Refinement and Insertion for Sparse Motion},
author={Choi, Jaehyun and Hur, Jiwan and Han, Gyojin and Yu, Jaemyung and Kim, Junmo},
booktitle={IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2026}
}
@inproceedings{shin2026ssg,
title={SSG: Scaled Spatial Guidance for Multi-Scale Visual Autoregressive Generation},
author={Shin, Youngwoo and Hur, Jiwan and Kim, Junmo},
booktitle={International Conference on Learning Representations (ICLR)},
year={2026}
}
@inproceedings{kim2026inlier,
title={Inlier-Centric Post-Training Quantization for Object Detection Models},
author={Kim, Minsu and Lee, Dongyeun and Yu, Jaemyung and Hur, Jiwan and Kim, Giseop and Kim, Junmo},
booktitle={International Conference on Learning Representations (ICLR)},
year={2026}
}
@inproceedings{lee2025frequency,
title={Frequency-Aware Token Reduction for Efficient Vision Transformer},
author={Lee, Dong-Jae and Hur, Jiwan and Choi, Jaehyun and Yu, Jaemyung and Kim, Junmo},
booktitle={Advances in Neural Information Processing Systems (NeurIPS)},
year={2025}
}
@Article{hur2024unlocking,
title={Unlocking the Capabilities of Masked Generative Models for Image Synthesis via Self-Guidance},
author={Hur, Jiwan and Lee, Dong-Jae and Han, Gyojin and Choi, Jaehyun and Jeon, Yunho and Kim, Junmo},
journal={arXiv preprint arXiv:2410.13136},
year={2024}
}
@Article{hur2024unlocking,
title={Unlocking the Capabilities of Masked Generative Models for Image Synthesis via Self-Guidance},
author={Hur, Jiwan and Lee, Dong-Jae and Han, Gyojin and Choi, Jaehyun and Jeon, Yunho and Kim, Junmo},
journal={arXiv preprint arXiv:2410.13136},
year={2024}
}
@inproceedings{han2025learning,
title={Learning Neural Deformation Representation for 4D Dynamic Shape Generation},
author={Han, Gyojin and Hur, Jiwan and Choi, Jaehyun and Kim, Junmo},
booktitle={European Conference on Computer Vision},
pages={186--203},
year={2025},
organization={Springer}
}
@inproceedings{hur2024expanding,
title={Expanding Expressiveness of Diffusion Models with Limited Data via Self-Distillation based Fine-Tuning},
author={Hur, Jiwan and Choi, Jaehyun and Han, Gyojin and Lee, Dong-Jae and Kim, Junmo},
booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},
pages={5028--5037},
year={2024}
}
@inproceedings{han2023deep,
title={Deep cross-modal steganography using neural representations},
author={Han, Gyojin and Lee, Dong-Jae and Hur, Jiwan and Choi, Jaehyun and Kim, Junmo},
booktitle={2023 IEEE International Conference on Image Processing (ICIP)},
pages={1205--1209},
year={2023},
organization={IEEE}
}
@article{lee2023multi,
title={Multi-scale foreground-background separation for light field depth estimation with deep convolutional networks},
author={Lee, Jae Young and Hur, Jiwan and Choi, Jaehyun and Park, Rae-Hong and Kim, Junmo},
journal={Pattern Recognition Letters},
volume={171},
pages={138--147},
year={2023},
publisher={Elsevier}
}
@inproceedings{hur2023see,
title={I see-through you: A framework for removing foreground occlusion in both sparse and dense light field images},
author={Hur, Jiwan and Lee, Jae Young and Choi, Jaehyun and Kim, Junmo},
booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision},
pages={229--238},
year={2023}
}
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Template adapted from Jaehyun Choi, Siwei Zhang, Qianli Ma, and Jon Barron. |