arXiv Computer Vision
ReGround-Surg: Reliability-Guided Anchor Grounding for Referring Surgical Video Segmentation
Read the original on arXiv Computer Vision →The Flow has not summarised this story yet — read it at arXiv Computer Vision.
Related stories
arXiv Computer Vision
Aug 25
Dense Structural Priors for Sparse Functional Landmark Localization in Surgical Videos
The paper presents a method for localizing functional surgical landmarks—specifically instrument tips and anchors—in surgical videos without requiring manual pixel-level mask annotations. It leverages vision foundation models, such as SAM 3, to generate dense structural priors through zero‑shot, point‑prompted masks, and refines landmark predictions with a lightweight, coarse‑to‑fine multi‑frame network. Experiments on 7,867 clips from 60 videos show that the approach achieves F1 scores of 72.4% for tip and 58.0% for anchor localization, with ablations confirming the benefits of structural priors and refinement stages.
arXiv Computer Vision
Aug 26
Hierarchical Prototype-Memory Adaptation of SAM for Surgical Instrument Segmentation
arXiv:2608.24541v1 Announce Type: new Abstract: Surgical instrument segmentation (SIS) is fundamental for computer-assisted surgery, where reliable instrument masks enable precise scene understanding...
Hugging Face Trending Papers
Aug 25
Hierarchical Prototype-Memory Adaptation of SAM for Surgical Instrument Segmentation
Surgical instrument segmentation (SIS) is fundamental for computer-assisted surgery, where reliable instrument masks enable precise scene understanding and clinical assistance. Recently, adapting foun...
arXiv Machine Learning
Aug 4
Slot2Text: Object-Centric Visual Tokenization for Efficient and Spatially Traceable Surgical MLLMs
arXiv:2608. 01473v1 Announce Type: cross Abstract: Multimodal large language models (MLLM) for surgical scene understanding typically inject hundreds of dense visual tokens into a language model, leading to costly inference and limited spatial traceability for generated answers.
arXiv AI
Aug 24
Action-grounded tissue affordance enables anticipatory auto-framing that lowers surgeon cognitive workload during laparoscopic surgery
arXiv:2608.02471v2 Announce Type: replace-cross Abstract: In laparoscopy, surgeon gaze tracks where the instruments will act; easing this demand through visual attention modeling requires dense label...
arXiv Computer Vision
Aug 25
SurgTEMP: Temporal-Aware Surgical Video Question Answering with Text-guided Visual Memory for Laparoscopic Cholecystectomy
arXiv:2603.29962v4 Announce Type: replace Abstract: Surgical procedures are inherently complex and risky, requiring extensive expertise and constant focus to navigate evolving intraoperative scenes....