Research Groups

The Intelligent Computational imaging Lab (ICL) is rooted in computational imaging, where mathematically rigorous yet efficient optimization grounds every image in the physics of how it was measured. We carry that grounding into multimodal, multiscale representations and foundation models, designing algorithms that scale without giving up rigor. We close the loop with agents that act in the physical world and team with people, treating every input, measurement and human guidance alike, as valuable yet uncertain.

Computational & medical imaging;
AI for Signal processing;
Deep learning

H G Seo, B H Lee, M J Kim, D H Mah, J H Lee, S Y Chun, "Strong Helps Weak: Directional Cross-Modal Alignment Transfer in Multi-modal LLMs," Accepted at NeurIPS, 2026 (Spotlight)
J S Bang, D W Choi, D J Mun, S Y Chun, "FLINT: Coupling Proximal Initialization and Bounded Stochasticity for Flow-Matching Inverse Problems," Accepted at NeurIPS 2026
J H Jang, H Y Kim, C W Lee, J J Kim, S Y Chun, "HyFL-CLIP: Hyperbolic Fine-Tuning of CLIP for Robust Long-Context Understanding," ECCV 2026
J S Bang, D J Mun, H G Seo, S M Hong, S Y Chun, "Triadic Dynamics Aware Diffusion Posterior Sampling for Inverse Problems: Optimizing Guidance and Stochasticity Schedules," ICML 2026
G H Kim, J J Kim, S Y Jeon, J S Park, S Y Chun, "Human Interaction-Aware 3D Reconstruction from a Single Image," CVPR 2026 (Highlight)
H Y Kim, J H Jang, J J Kim, S Y Chun, "Uncertainty-guided Compositional Alignment with Part-to-Whole Semantic Representativeness in Hyperbolic Vision-Language Models," CVPR 2026 (Highlight)
H G Seo, B H Lee, J H Cho, S J Lim, S Y Chun, "Erasing Thousands of Concepts: Towards Scalable and Practical Concept Erasure for Text-to-Image Diffusion Models," CVPR 2026
W G Jeong, H G Seo, S Y Chun, "Training-free, Perceptually Consistent Low-Resolution Previews with High-Resolution Image for Efficient Workflows of Diffusion Models," CVPR 2026
W G Jeong, K R Lee, H G Seo, S Y Chun, "Training-free Mixed-Resolution Latent Upsampling for Spatially Accelerated Diffusion Transformers," Accepted at CVPR 2026 (Highlight)
S M Hong*, J J Kim*, D H Kim, I S Chung, S Y Chun, "DiffBMP: Differentiable Rendering with Bitmap Primitives," CVPR 2026