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

6 citations · 6 across the 3 of their papers we have counts for

collaborators

22 papers

cs.CV2026

SurgNarrator: A Generative Retrieval Framework for Surgical Video Understanding

Yuqing Feng, Jiawei Ma, Kevin Qinghong Lin +6

Surgical procedures unfold as structured and recurring clinical events, whose real-time understanding via intraoperative surgical videos is critical for intraoperative decision-mak…

cs.CV2026

HyperVLP: Enhancing Hierarchical Surgical Video-Language Pre-training in Hyperbolic Space

Yaojun Hu, Kun Yuan, Nassir Navab +3

Surgical vision-language foundation models typically adopt educational materials, such as surgical lecture videos, to transfer surgical knowledge encoded in language into visual re…

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

CliPPER: Contextual Video-Language Pretraining on Long-form Intraoperative Surgical Procedures for Event Recognition

Florian Stilz, Vinkle Srivastav, Nassir Navab +1

Video-language foundation models have proven to be highly effective in zero-shot applications across a wide range of tasks. A particularly challenging area is the intraoperative su…

cs.CV2026

From Panel to Pixel: Zoom-In Vision-Language Pretraining from Biomedical Scientific Literature

Kun Yuan, Min Woo Sun, Zhen Chen +7

There is a growing interest in developing strong biomedical vision-language models. A popular approach to achieve robust representations is to use web-scale scientific data. Howeve…

cs.CV2026

DSeq-JEPA: Discriminative Sequential Joint-Embedding Predictive Architecture

Xiangteng He, Shunsuke Sakai, Shivam Chandhok +5

Recent advances in self-supervised visual representation learning have demonstrated the effectiveness of predictive latent-space objectives for learning transferable features. In p…