5 accepted papers
6D pose estimation is a key technology in computer vision and robotic manipulation. However, many methods remain heavily dependent on CAD models that are difficult to obtain. Object-level 3D reconstruction provides an alternative route, and 3D Gaussian Splatting (3DGS) shows convincing potential owi
In structured light systems, the accuracy of measurement notably diminishes when assessing complex texture objects, especially encountering boundaries between various colors. To address this challenge, this paper meticulously analyzes and establishes an error model, elaborating the correlation betwe…
In structured light systems, measurement accuracy tends to decline significantly when evaluating complex textured surfaces, particularly at boundaries between different colors. To address this issue, this paper conducts a detailed analysis to develop an error model that illustrates the relationship…
Hybrid monocular visual odometry, which combines the advantages of learning-based and geometry-based methods, has gained widespread attention for its superior robustness and accuracy. Recent works use networks to predict optical flow to establish pixel correspondences between images while retaining
Object pose estimation in open-world scenarios is a critical challenge in robotics, virtual reality, and autonomous driving. In this letter, we introduce SamPose, a novel framework designed to achieve model-free 6DoF pose estimation of any target object in open-world environments using only a single