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Found 8 papers, 1 papers with code
Adaptive Annealing for Robust Geometric Estimation
Geometric estimation problems in vision are often solved via minimization of statistical loss functions which account for the presence of outliers in the observations.
Efficient and Robust Registration on the 3D Special Euclidean Group
Our approach significantly outperforms the state-of-the-art robust 3D registration method based on a line process in terms of both speed and accuracy.
3DRegNet: A Deep Neural Network for 3D Point Registration
Given a set of 3D point correspondences, we build a deep neural network to address the following two challenges: (i) classification of the point correspondences into inliers/outliers, and (ii) regression of the motion parameters that align the scans into a common reference frame.
A Face Fairness Framework for 3D Meshes
In this paper, we present a face fairness framework for 3D meshes that preserves the regular shape of faces and is applicable to a variety of 3D mesh restoration tasks.
Multi-View Non-Rigid Refinement and Normal Selection for High Quality 3D Reconstruction
In this paper, we present a complete pipeline for such depth-normal fusion.
Photometric Refinement of Depth Maps for Multi-Albedo Objects
The method of this paper does not require the constant albedo assumption and we believe it is the first work of its kind to handle objects with arbitrary albedo under uncalibrated illumination.
Noise in Structured-Light Stereo Depth Cameras: Modeling and its Applications
Depth maps obtained from commercially available structured-light stereo based depth cameras, such as the Kinect, are easy to use but are affected by significant amounts of noise.
High Quality Photometric Reconstruction using a Depth Camera
Firstly, instead of using an extra RGB camera, we use the infra-red (IR) camera of the depth camera system itself to directly obtain high resolution photometric information.
