3 citations · 4 across the 5 of their papers we have counts for
7 papers · 1 filter
StackTok: Accelerating VLMs Inference with Budget-Adaptive Visual Token Selection
Zhenbin Wang, Lei Zhang, Lituan Wang +3
Increasing image resolution produces ever-longer visual-token sequences in vision-language models (VLMs), substantially raising their inference cost. To reduce this overhead withou…
Boundary-Aware Test-Time Adaptation for Zero-Shot Medical Image Segmentation
Chenlin Xu, Lei Zhang, Lituan Wang +5
Due to the scarcity of annotated data and the substantial computational costs of model, conventional tuning methods in medical image segmentation face critical challenges. Current…
EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation
Wang Lituan, Zhang Lei, Wang Yan +3
Weakly-supervised medical image segmentation is gaining traction as it requires only rough annotations rather than accurate pixel-to-pixel labels, thereby reducing the workload for…
Optical Flow Representation Alignment Mamba Diffusion Model for Medical Video Generation
Zhenbin Wang, Lei Zhang, Lituan Wang +2
Medical video generation models are expected to have a profound impact on the healthcare industry, including but not limited to medical education and training, surgical planning, a…
Soft Masked Mamba Diffusion Model for CT to MRI Conversion
Zhenbin Wang, Lei Zhang, Lituan Wang +1
Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) are the predominant modalities utilized in the field of medical imaging. Although MRI capture the complexity of anatom…
PCLMix: Weakly Supervised Medical Image Segmentation via Pixel-Level Contrastive Learning and Dynamic Mix Augmentation
Yu Lei, Haolun Luo, Lituan Wang +2
In weakly supervised medical image segmentation, the absence of structural priors and the discreteness of class feature distribution present a challenge, i.e., how to accurately pr…