Foundation and multimodal Models in Computational Imaging
Abstract:
This session targets recent advances in foundation and multimodal models for computational imaging, such as text+image models, as well as related topics like diffusion models for inverse problems.
Organiser & chair: Jong Chul Ye
Session Schedule
- 8:00 - 8:20
- Invited talk - Diffusion Models as a Foundation Model for Inverse Problems
- Jong Chul Ye
- 8:20 - 8:40
- Invited talk - In Search of Good Training Sets for Foundation Models in Medical Imaging
- Reinhard Heckel
- 8:40 - 9:00
- Invited talk - MediConfusion: How much can you trust your AI doctor?
- Mahdi Soltanolkotabi
- 9:00 - 9:20
- Invited talk - Building Vision-Language Models for Radiology
- Akshay Chaudhari
- 9:20 - 9:40
- Invited talk - 3D Computer Vision in the Age of Deep Learning
- Daniel Cremers
- 9:40 - 11:00
- Invited poster - Distribution Shifts and Adaptation in Computational Imaging
- Salman Asif
- 9:40 - 11:00
- Invited poster - Ambient Diffusion: Learning Clean Distributions from Corrupted Data
- Giannis Daras
- 9:40 - 11:00
- Contributed poster - TBC
- TBC
- 9:40 - 11:00
- Contributed poster - TBC
- TBC
- 9:40 - 11:00
- Contributed poster - TBC
- TBC