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Found 4 papers, 2 papers with code
Recent Trends in 3D Reconstruction of General Non-Rigid Scenes
Reconstructing models of the real world, including 3D geometry, appearance, and motion of real scenes, is essential for computer graphics and computer vision.
Neural Parametric Gaussians for Monocular Non-Rigid Object Reconstruction
However, owing to the ill-posed nature of this problem, there has been no solution that can provide consistent, high-quality novel views from camera positions that are significantly different from the training views.
ManhattanSLAM: Robust Planar Tracking and Mapping Leveraging Mixture of Manhattan Frames
In this paper, a robust RGB-D SLAM system is proposed to utilize the structural information in indoor scenes, allowing for accurate tracking and efficient dense mapping on a CPU.
RGB-D SLAM with Structural Regularities
This work proposes a RGB-D SLAM system specifically designed for structured environments and aimed at improved tracking and mapping accuracy by relying on geometric features that are extracted from the surrounding.
Robotics
