Fast Data Generation for Training Deep-Learning 3D Reconstruction Approaches for Camera Arrays
In the last decade, many neural network algorithms have been proposed to solve depth reconstruction. Our focus is on reconstruction from images captured by multi-camera arrays which are a grid of vertically and horizontally aligned cameras that are uniformly spaced. Training these networks using sup...
Main Authors: | Théo Barrios, Stéphanie Prévost, Céline Loscos |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-12-01
|
Series: | Journal of Imaging |
Subjects: | |
Online Access: | https://www.mdpi.com/2313-433X/10/1/7 |
Similar Items
-
Fast 3D Face Reconstruction from a Single Image Using Different Deep Learning Approaches for Facial Palsy Patients
by: Duc-Phong Nguyen, et al.
Published: (2022-10-01) -
Optimal Coherent Point Selection for 3D Quality Inspection from Silhouette-Based Reconstructions
by: Javier Pérez Soler, et al.
Published: (2023-10-01) -
External Anatomical Shapes Reconstruction from Turntable Image Sequences using a Single off-the-shelf Camera
by: Teresa Azevedo, et al.
Published: (2008-02-01) -
Occluded-Object 3D Reconstruction Using Camera Array Synthetic Aperture Imaging
by: Zhao Pei, et al.
Published: (2019-01-01) -
3D Metrology Using One Camera with Rotating Anamorphic Lenses
by: Xiaobo Chen, et al.
Published: (2022-11-01)