PA-MVSNet: Sparse-to-Dense Multi-View Stereo With Pyramid Attention
Multi-view based 3D reconstruction aims to obtain 3D structure information of objects in space through two-dimensional images. In this paper, we propose a new multi-view stereo network that can robustly reconstruct the scene. To enhance the feature representation ability of Point-MVSNet, a pyramid a...
Main Authors: | Ke Zhang, Mengyu Liu, Jinlai Zhang, Zhenbiao Dong |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2021-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9352763/ |
Similar Items
-
HighRes-MVSNet: A Fast Multi-View Stereo Network for Dense 3D Reconstruction From High-Resolution Images
by: Rafael Weilharter, et al.
Published: (2021-01-01) -
Multi-Scale Dense Attention Network for Stereo Matching
by: Yuhui Chang, et al.
Published: (2020-11-01) -
Generation of Stereo Images Based on a View Synthesis Network
by: Yuan-Mau Lo, et al.
Published: (2020-04-01) -
Multi-Dimensional Residual Dense Attention Network for Stereo Matching
by: Guanghui Zhang, et al.
Published: (2019-01-01) -
A Multi-View Dense Point Cloud Generation Algorithm Based on Low-Altitude Remote Sensing Images
by: Zhenfeng Shao, et al.
Published: (2016-05-01)