BISPL- BioImaging, Signal Processing & Learning Lab @ KAIST AI
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Latest Research Highlight
DreamSampler:Unifying Diffusion Sampling and Score Distillation for Image Manipulation

Kim et al,  2024 European Conference on Computer Vision (ECCV).

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Five papers accepted for ECCV 2024!!

7/2/2024

 
Congratulations!  The following five papers from BISPL are accepted for ECCV 2024.
  1. Hyeonho Jeong, Jinho Chang, Geon Yeong Park, Jong Chul Ye. "DreamMotion: Space-Time Self-Similarity Score Distillation for Zero-Shot Video Editing",  in Proceedings of 2024 European Conference on Computer Vision (ECCV).
  2. Soobin Um, and Jong Chul Ye "Self-Guided Generation of Minority Samples Using Diffusion Models",  in Proceedings of 2024 European Conference on Computer Vision (ECCV).
  3. Hyungjin Chung and Jong Chul Ye, "Deep Diffusion Image Prior for Efficient OOD Adaptation in 3D Inverse Problems",  in Proceedings of 2024 European Conference on Computer Vision (ECCV).
  4. Kwanyoung Kim, Yujin Oh, and Jong Chul Ye, "OTSeg: Multi-prompt Sinkhorn Attention for Zero-Shot Semantic Segmentation",  in Proceedings of 2024 European Conference on Computer Vision (ECCV).
  5. Jeongsol Kim, Geon Yeong Park, and Jong Chul Ye, "DreamSampler: Unifying Diffusion Sampling and Score Distillation for Image Manipulation", in Proceedings of 2024 European Conference on Computer Vision (ECCV).

Two papers are accepted for ICML 2024!

5/2/2024

 
Congratulations!  The following two papers have been accepted for ICML 2024.  
  1. Sangmin Lee, Abbas Mammadov, Jong Chul Ye, "Defining Neural Network Architecture through Polytope Structures of Dataset",  in the Proceedings of The  International Conference on Machine Learning (ICML), 2024.
  2. Hyungjin Chung, Jong Chul Ye, Peyman Milanfar, Mauricio Delbracio, "Prompt-tuning latent diffusion models for inverse problems",   in the Proceedings of The  International Conference on Machine Learning (ICML), 2024.
This year so far, we have 13 top-tier AI conference papers  (6 ICLR,  4 CVPR, 2 ICML, 1 AAA) and 7 journal papers (Nature Communications, etc.)

Our Paper on Chemical Foundation Models Appeared on Nature Comm!

3/14/2024

 
Congratulations! The following paper appears on Nature Communication!
  1. Jinho Chang and Jong Chul Ye,"Bidirectional Generation of Structure and Properties Through a Single Molecular Foundation Model",Nat Commun 15, 2323 (2024).
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Four papers got accepted for CVPR 2024!

2/26/2024

 
Congratulations! The following four papers are accepted for CVPR 2024.
  1. Hyelin Nam, Gihyun Kwon, Geon Yeong Park, Jong Chul Ye,"Contrastive Denoising Score for Text-guided Latent Diffusion Image Editing", in the Proceedings of The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
  2. Hyeonho Jeong, Geon Yeong Park, Jong Chul Ye, "One-Shot Video Motion Customization using Temporal Attention Adaption for Text-to-Video Diffusion Models", in the Proceedings of The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
  3. Geon Yeong Park, Chanyong Jung, Sangmin Lee, Jong Chul Ye, Sang Wan Lee,"Self-supervised debiasing using low rank regularization", in the Proceedings of The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
  4. Gihyun Kwon, Simon Jenni, Dingzeyu Li, Joon-Young Lee, Jong Chul Ye, Fabian Caba Heilbron, "Concept Weaver: Enabling Multi-Concept Fusion in Text-to-Image Models",  in the Proceedings of The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.

Six papers accepted for ICLR 2024!

1/17/2024

 
Congratulations!  The following six papers from BISPL have been accepted for presentation at the 2024 International Conference on Learning Representations (ICLR).
  1. Hyeonho Jeong, Jong Chul Ye,"Ground-A-Video: Zero-shot Grounded Video Editing using Text-to-image Diffusion Models", International Conference on Learning Representations (ICLR), 2024.
  2. Hyungjin Chung, Suhyeon Lee, Jong Chul Ye,,  "Decomposed Diffusion Sampler for Accelerating Large-Scale Inverse Problems", International Conference on Learning Representations (ICLR), 2024.
  3. Beomsu Kim, Gihyun Kwon, Kwanyoung Kim, Jong Chul Ye,"Unpaired Image-to-Image Translation via Neural Schrödinger Bridge",  International Conference on Learning Representations (ICLR), 2024.
  4. Soobin Um, Suhyeon Lee, Jong Chul Ye,"Don't Play Favorites: Minority Guidance for Diffusion Models", International Conference on Learning Representations (ICLR), 2024.
  5. JangHo Park, Gihyun Kwon, Jong Chul Ye,"ED-NeRF: Efficient Text-Guided Editing of 3D Scene With Latent Space NeRF", International Conference on Learning Representations (ICLR), 2024.
  6. Suhyeon Lee, Won Jun Kim, Jinho Chang, Jong Chul Ye,"LLM-CXR: Instruction-Finetuned LLM for CXR Image Understanding and Generation",International Conference on Learning Representations (ICLR), 2024.
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    BISPL@KAIST AI

    BISPL is a group of people at KAIST who are eager to dedicate their time and effort to investigate the beauty of bio- and medical imaging with the help of mathematics, machine learning, and physics.
ABOUT US
Our research activities are primarily focused on the signal processing and machine learning  for high-resolution high-sensitivity image reconstruction from real world bio-medical imaging systems. Such problems pose interesting challenges that often lead to investigations of fundamental problems in various branches of physics, mathematics, signal processing, biology, and medicine. While most of the biomedical imaging researchers are interested in addressing this problem using off-the-self tools from signal processing, machine learning, statistics, and optimization and combining their domain-specific knowledge, our approaches are unique in the sense that I believe that actual bio-medical imaging applications are a source of endless inspiration for new mathematical theories and we are eager to solve both specific applications and application-inspired fundamental theoretical problems. 
CONTACT US
Bio Imaging. Signal Processing & Learning
Graduate School of AI
KAIST
291 Daehak-ro, Yuseong-gu
Daejeon 305-701, Korea

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All Rights Reserved.
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