3 accepted papers
Loop closing is critically important in Simultaneous Localization and Mapping (SLAM) due to its ability to correct accumulated localization errors. However, existing methods are hindered by the difficulty of acquiring pose labels and the unreliability of ground truth data. In this paper, we propose
While human vision inherently achieves robust cross-domain depth estimation through binocular coordination, robotic systems employing stereo matching still confront significant challenges in maintaining robustness across domains when performing real-time environmental depth perception. Furthermore,
Estimating the 6-DoF camera pose of an image with respect to a 3D scene model, known as visual localization, is a fundamental problem in many computer vision and robotics tasks. Among various visual localization methods, the direct 2D-3D matching method has become the preferred method for many pract…