1 nov. 2019 computer graphics and machine learning communities. Since 2015
17 sept. 2021 Keywords: voxels; geometric modeling; 3D surface reconstruction; variational autoencoders; deep learning. 1. Introduction.
The 3D reconstruction problem. ? Methods Issues and challenges. ? Deep learning for 3D reconstruction. ? Background: deep neural nets.
With the advent of deep neural networks learning-based approaches for 3D reconstruction have gained popularity. However
Deep learning has revolutionized computer vision through recent developments on tasks in this field. Although these developments initially started with 2D
2 août 2022 This paper serves as a review of recent literature on 3D reconstruction from a single view with a focus on deep learning methods from 2018 ...
3D reconstruction using deep learning: a survey. Yiwei Jin Diqiong Jiang
1: Reconstruction performed by our Deep Local Shapes (DeepLS) of the Burghers of Calais scene [57]. DeepLS represents surface geometry as a sparse set of local
31 mars 2019 It proposes an end-to-end deep learning method with a lightweight and effective neural network to reconstruct multiple high-fidelity. 3D organ ...