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20242026
most citedIntuitive Surgical SurgToolLoc and SurgVU Challenges Results: 2022-2025

6 citations · 11 across the 16 of their papers we have counts for

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cs.CV2026

Parameter-Efficient Adaptation of SAM3 for Prompt-Driven Surgical Concept Segmentation

Changjing Liu, Yiming Huang, Beilei Cui +5

Efficient surgical segmentation empowers clinical diagnosis, intraoperative monitoring, and downstream robotic pipelines for reconstruction and simulation. Although prompt-driven f…

cs.CV2026

GeoCFNet: Geometry-Aware Confidence Field Network for Robot-Assisted Endoscopic Submucosal Dissection

Rui Tang, Guankun Wang, Long Bai +5

Advanced surgical robotics has made robot-assisted endoscopic submucosal dissection (ESD) a promising approach for the en-bloc resection of large lesions, with the potential to red…

cs.CV2026

SurgOnAir: Hierarchy-Aware Real-Time Surgical Video Commentary

Jingyi He, Yue Zhou, Long Bai +3

Understanding surgical workflow in real time is fundamental for intelligent surgical embodiment, where AI systems continuously perceive and respond as surgery proceeds. In the oper…

cs.CV20266 cited

Intuitive Surgical SurgToolLoc and SurgVU Challenges Results: 2022-2025

Aneeq Zia, Max Berniker, Rogerio Garcia Nespolo +153

Robotic assisted (RA) surgery promises to transform surgical intervention. Intuitive Surgical is committed to fostering these changes and the machine learning models and algorithms…

cs.CV2026

EndoGSim: Physics-Aware 4D Dynamic Endoscopic Scene Simulations via MLLM-Guided Gaussian Splatting

Changjing Liu, Yiming Huang, Long Bai +2

In robot-assisted minimally invasive surgery, high-fidelity dynamic endoscopic scene reconstruction and simulation are crucial to enhancing downstream tasks and advancing surgical…

cs.CV2026

TR2M: Transferring Monocular Relative Depth to Metric Depth with Language Descriptions and Dual-Level Scale-Oriented Contrast

Beilei Cui, Yiming Huang, Long Bai +1

This work presents a generalizable framework to transfer relative depth to metric depth. Current monocular depth estimation methods are mainly divided into metric depth estimation…