SurfSurg6D: Geometry Consistent Dense Correspondence for Textureless Surgical Instrument Pose Estimation
2026-05-25 • Computer Vision and Pattern Recognition
Computer Vision and Pattern Recognition
AI summaryⓘ
The authors address the challenge of accurately figuring out the position and orientation (pose) of surgical tools during operations, which is hard because the tools often look similar and can be partially hidden. To help, they created a new dataset called SynSurg6D to provide more varied examples for training. They also developed a new method called SurfSurg6D that uses detailed matching techniques to estimate poses from regular video images alone. Their experiments show that their dataset improves existing methods, and their new approach performs better and more reliably than prior ones.
pose estimationsurgical instrumentsRGB imagingdense correspondencedataset creationrobotic surgerycomputer visionEndoVis2018SurgPosemachine learning
Authors
Daiyun Shen, Shuojue Yang, Chang Han Low, Qian Li, Mengya Xu, Qi Dou, Yueming Jin
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. Experimental results on the SurgRIPE, EndoVis2018 and SurgPose datasets demonstrate that the introduction of our generated dataset SynSurg6D is able to diversify the pose distributions, thus enhancing the performance of existing approaches. Furthermore, SurfSurg6D outperforms existing methods, providing a robust solution for precise and efficient RGB-only pose estimation.