collaborators

7 papers

eess.IV2026

UniSurgSAM: A Unified Promptable Model for Reliable Surgical Video Segmentation

Haofeng Liu, Ziyue Wang, Alex Y. W. Kong +6

Surgical video segmentation is fundamental to computer-assisted surgery. In practice, surgeons need to dynamically specify targets throughout extended procedures, using heterogeneo…

cs.CV2026

SurgFed: Language-guided Multi-Task Federated Learning for Surgical Video Understanding

Zheng Fang, Ziwei Niu, Ziyue Wang +5

Surgical scene Multi-Task Federated Learning (MTFL) is essential for robot-assisted minimally invasive surgery (RAS) but remains underexplored in surgical video understanding due t…

cs.MA2025

CARES: Collaborative Agentic Reasoning for Error Detection in Surgery

Chang Han Low, Zhu Zhuo, Ziyue Wang +11

Robotic-assisted surgery (RAS) introduces complex challenges that current surgical error detection methods struggle to address effectively due to limited training data and methodol…

cs.CV2025

Structure Matters: Revisiting Boundary Refinement in Video Object Segmentation

Guanyi Qin, Ziyue Wang, Daiyun Shen +5

Given an object mask, Semi-supervised Video Object Segmentation (SVOS) technique aims to track and segment the object across video frames, serving as a fundamental task in computer…

cs.CV2025

ReSurgSAM2: Referring Segment Anything in Surgical Video via Credible Long-term Tracking

Haofeng Liu, Mingqi Gao, Xuxiao Luo +4

Surgical scene segmentation is critical in computer-assisted surgery and is vital for enhancing surgical quality and patient outcomes. Recently, referring surgical segmentation is…

cs.AI2025

MedAgent-Pro: Towards Evidence-based Multi-modal Medical Diagnosis via Reasoning Agentic Workflow

Ziyue Wang, Junde Wu, Linghan Cai +4

In modern medicine, clinical diagnosis relies on the comprehensive analysis of primarily textual and visual data, drawing on medical expertise to ensure systematic and rigorous rea…