RFFCE: Residual Feature Fusion and Confidence Evaluation Network for 6DoF Pose Estimation
Qiwei Meng,Shanshan Ji,Shiqiang Zhu,Tianlei Jin,Te Li,Jason Gu,Wei Song,Qiwei Meng,Shanshan Ji,Shiqiang Zhu,Tianlei Jin,Te Li,Jason Gu,Wei Song
In this paper, we propose a novel RGBD-based object 6DoF pose estimation network - RFFCE. It is a two-stage method that firstly leverages deep neural networks for feature extraction and object points matching, and then the geometric principles are utilized for final pose computation. Our approach consists of three primary innovations: residual feature fusion for representative RGBD feature extract...
