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Found 5 papers, 4 papers with code
RPBA -- Robust Parallel Bundle Adjustment Based on Covariance Information
We show that our novel approach is suitable for robust parallel bundle adjustment and demonstrate its capabilities in comparison to the basic consensus-based approach as well as a state-of-the-art parallel implementation of bundle adjustment.
CALVIS: chest, waist and pelvis circumference from 3D human body meshes as ground truth for deep learning
In this paper we present CALVIS, a method to calculate $\textbf{C}$hest, w$\textbf{A}$ist and pe$\textbf{LVIS}$ circumference from 3D human body meshes.
A Neural-Symbolic Architecture for Inverse Graphics Improved by Lifelong Meta-Learning
We follow the idea of formulating vision as inverse graphics and propose a new type of element for this task, a neural-symbolic capsule.
Adding Intuitive Physics to Neural-Symbolic Capsules Using Interaction Networks
Many current methods to learn intuitive physics are based on interaction networks and similar approaches.
Modeling Urban Scenes From Pointclouds
In contrast to existing approaches, MUSP is robust, scalable and provides a more complete description by not making a Manhattan-World assumption and modeling both buildings (with polyhedra) as well as the non-planar ground (using NURBS).
