85 citations · 86 across the 4 of their papers we have counts for
4 papers
SAM3-UNet: Simplified Adaptation of Segment Anything Model 3
Xinyu Xiong, Zihuang Wu, Lei Lu +1
In this paper, we introduce SAM3-UNet, a simplified variant of Segment Anything Model 3 (SAM3), designed to adapt SAM3 for downstream tasks at a low cost. Our SAM3-UNet consists of…
SAM2-UNeXT: An Improved High-Resolution Baseline for Adapting Foundation Models to Downstream Segmentation Tasks
Xinyu Xiong, Zihuang Wu, Lei Zhang +3
Recent studies have highlighted the potential of adapting the Segment Anything Model (SAM) for various downstream tasks. However, constructing a more powerful and generalizable enc…
PDC-Net: Pattern Divide-and-Conquer Network for Pelvic Radiation Injury Segmentation
Xinyu Xiong, Wuteng Cao, Zihuang Wu +4
Accurate segmentation of Pelvic Radiation Injury (PRI) from Magnetic Resonance Images (MRI) is crucial for more precise prognosis assessment and the development of personalized tre…
SAM2-UNet: Segment Anything 2 Makes Strong Encoder for Natural and Medical Image Segmentation
Xinyu Xiong, Zihuang Wu, Shuangyi Tan +6
Image segmentation plays an important role in vision understanding. Recently, the emerging vision foundation models continuously achieved superior performance on various tasks. Fol…