SurfSurg6D: Geometry Consistent Dense Correspondence for Textureless Surgical Instrument Pose Estimation 文章

ArXiv CS.CV2026-05-26NEWSen作者: Daiyun Shen, Shuojue Yang, Chang Han Low, Qian Li, Mengya Xu, Qi Dou, Yueming Jin

摘要

arXiv:2605.25598v1 Announce Type: new Abstract: Surgical instrument pose estimation provides crucial information for promising applications, including autonomous robotic surgery, skill assessment, and standardization of surgical workflow. However, this task remains highly challenging due to high precision requirements, frequent occlusions, textureless instruments, scarcity of depth information and very limited annotated data. These constraints often lead to unsatisfactory performance when employing general object pose estimation approaches to surgical scenarios. To address these issues, we first construct a new dataset SynSurg6D, to alleviate the data shortage in this task. We further propose SurfSurg6D, a dense-correspondence framework tailored for surgical instrument pose estimation.