“My attended work SAMora Has Been Accepted by ICCV 2025!”

🎉 Excited to share that the paper I contributed as co-author “SAMora: Enhancing SAM through Hierarchical Self-Supervised Pre-Training for Medical Images” has been accepted to ICCV 2025!

In this work, we propose SAMora, a novel framework that boosts the performance of the Segment Anything Model (SAM) on medical images through a hierarchical self-supervised pre-training strategy. Our approach brings significant improvements to medical segmentation tasks where labeled data is scarce.

Thank you to all co-authors and collaborators for making this possible！