1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CV2025
When Tracking Fails: Analyzing Failure Modes of SAM2 for Point-Based Tracking in Surgical Videos
Woowon Jang, Jiwon Im, Juseung Choi +3
Video object segmentation (VOS) models such as SAM2 offer promising zero-shot tracking capabilities for surgical videos using minimal user input. Among the available input types, p…
cs.LG2025
Toward Using Machine Learning as a Shape Quality Metric for Liver Point Cloud Generation
Khoa Tuan Nguyen, Gaeun Oh, Ho-min Park +5
While 3D medical shape generative models such as diffusion models have shown promise in synthesizing diverse and anatomically plausible structures, the absence of ground truth make…
cs.CV2025★ 1 cited
Revisiting the Evaluation Bias Introduced by Frame Sampling Strategies in Surgical Video Segmentation Using SAM2
Utku Ozbulak, Seyed Amir Mousavi, Francesca Tozzi +4
Real-time video segmentation is a promising opportunity for AI-assisted surgery, offering intraoperative guidance by identifying tools and anatomical structures. Despite growing in…