Planercnn: 3d plane detection and reconstruction from a single image
This paper proposes a deep neural architecture, PlaneRCNN, that detects and reconstructs
piecewise planar regions from a single RGB image. PlaneRCNN employs a variant of Mask …
piecewise planar regions from a single RGB image. PlaneRCNN employs a variant of Mask …
Deep implicit moving least-squares functions for 3D reconstruction
Point set is a flexible and lightweight representation widely used for 3D deep learning.
However, their discrete nature prevents them from representing continuous and fine …
However, their discrete nature prevents them from representing continuous and fine …
Guiding monocular depth estimation using depth-attention volume
Recovering the scene depth from a single image is an ill-posed problem that requires
additional priors, often referred to as monocular depth cues, to disambiguate different 3D …
additional priors, often referred to as monocular depth cues, to disambiguate different 3D …
End-to-end wireframe parsing
We present a conceptually simple yet effective algorithm to detect wireframes in a given
image. Compared to the previous methods which first predict an intermediate heat map and …
image. Compared to the previous methods which first predict an intermediate heat map and …
Structure-slam: Low-drift monocular slam in indoor environments
In this letter a low-drift monocular SLAM method is proposed targeting indoor scenarios,
where monocular SLAM often fails due to the lack of textured surfaces. Our approach …
where monocular SLAM often fails due to the lack of textured surfaces. Our approach …