3 papers
cs.CV2024
PASS:Test-Time Prompting to Adapt Styles and Semantic Shapes in Medical Image Segmentation
Chuyan Zhang, Hao Zheng, Xin You +2
Test-time adaptation (TTA) has emerged as a promising paradigm to handle the domain shifts at test time for medical images from different institutions without using extra training…
cs.CV2024
RESTORE: Towards Feature Shift for Vision-Language Prompt Learning
Yuncheng Yang, Chuyan Zhang, Zuopeng Yang +6
Prompt learning is effective for fine-tuning foundation models to improve their generalization across a variety of downstream tasks. However, the prompts that are independently opt…
cs.CV2023
AC-Norm: Effective Tuning for Medical Image Analysis via Affine Collaborative Normalization
Chuyan Zhang, Yuncheng Yang, Hao Zheng +1
Driven by the latest trend towards self-supervised learning (SSL), the paradigm of "pretraining-then-finetuning" has been extensively explored to enhance the performance of clinica…