61 citations · 102 across the 21 of their papers we have counts for
4 papers · 1 filter
Learnable Prompting SAM-induced Knowledge Distillation for Semi-supervised Medical Image Segmentation
Kaiwen Huang, Tao Zhou, Huazhu Fu +4
The limited availability of labeled data has driven advancements in semi-supervised learning for medical image segmentation. Modern large-scale models tailored for general segmenta…
Exploring the Interplay Between Video Generation and World Models in Autonomous Driving: A Survey
Ao Fu, Yi Zhou, Tao Zhou +5
World models and video generation are pivotal technologies in the domain of autonomous driving, each playing a critical role in enhancing the robustness and reliability of autonomo…
SimTxtSeg: Weakly-Supervised Medical Image Segmentation with Simple Text Cues
Yuxin Xie, Tao Zhou, Yi Zhou +1
Weakly-supervised medical image segmentation is a challenging task that aims to reduce the annotation cost while keep the segmentation performance. In this paper, we present a nove…
MM-Retinal: Knowledge-Enhanced Foundational Pretraining with Fundus Image-Text Expertise
Ruiqi Wu, Chenran Zhang, Jianle Zhang +3
Current fundus image analysis models are predominantly built for specific tasks relying on individual datasets. The learning process is usually based on data-driven paradigm withou…