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

6 citations · 6 across the 1 of their papers we have counts for

collaborators
Showing cs.CVShow all

7 papers · 1 filter

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.CV2025

Multimodal Graph Representation Learning for Robust Surgical Workflow Recognition with Adversarial Feature Disentanglement

Long Bai, Boyi Ma, Ruohan Wang +8

Surgical workflow recognition is vital for automating tasks, supporting decision-making, and training novice surgeons, ultimately improving patient safety and standardizing procedu…

cs.CV2025

Learning to Efficiently Adapt Foundation Models for Self-Supervised Endoscopic 3D Scene Reconstruction from Any Cameras

Beilei Cui, Long Bai, Mobarakol Islam +8

Accurate 3D scene reconstruction is essential for numerous medical tasks. Given the challenges in obtaining ground truth data, there has been an increasing focus on self-supervised…

cs.CV2025

Surgical-LVLM: Learning to Adapt Large Vision-Language Model for Grounded Visual Question Answering in Robotic Surgery

Guankun Wang, Long Bai, Wan Jun Nah +7

Recent advancements in Surgical Visual Question Answering (Surgical-VQA) and related region grounding have shown great promise for robotic and medical applications, addressing the…

cs.CV2024

Surgical-VQLA++: Adversarial Contrastive Learning for Calibrated Robust Visual Question-Localized Answering in Robotic Surgery

Long Bai, Guankun Wang, Mobarakol Islam +3

Medical visual question answering (VQA) bridges the gap between visual information and clinical decision-making, enabling doctors to extract understanding from clinical images and…

cs.CV2024

SAM 2 in Robotic Surgery: An Empirical Evaluation for Robustness and Generalization in Surgical Video Segmentation

Jieming Yu, An Wang, Wenzhen Dong +5

The recent Segment Anything Model (SAM) 2 has demonstrated remarkable foundational competence in semantic segmentation, with its memory mechanism and mask decoder further addressin…