DEGAN: Detail-Enhanced Generative Adversarial Network for Monocular Depth-Based 3D Reconstruction
Abstract
References
Index Terms
- DEGAN: Detail-Enhanced Generative Adversarial Network for Monocular Depth-Based 3D Reconstruction
Recommendations
Depth map prediction from a single image with generative adversarial nets
AbstractA depth map is a fundamental component of 3D construction. Depth map prediction from a single image is a challenging task in computer vision. In this paper, we consider the depth prediction as an image-to-image task and propose an adversarial ...
Monocular Camera Based Real-Time Dense Mapping Using Generative Adversarial Network
MM '18: Proceedings of the 26th ACM international conference on MultimediaMonocular simultaneous localization and mapping (SLAM) is a key enabling technique for many computer vision and robotics applications. However, existing methods either can obtain only sparse or semi-dense maps in highly-textured image areas or fail to ...
3D shape reconstruction from multifocus image fusion using a multidirectional modified Laplacian operator
Highlights- The feasibility of combining multifocus image fusion and shape-from-focus methods to obtain real 3D reconstruction results is introduced.
AbstractMultifocus image fusion techniques primarily emphasize human vision and machine perception to evaluate an image, which often ignore depth information contained in the focus regions. In this paper, a novel 3D shape reconstruction ...
Comments
Information & Contributors
Information
Published In
![cover image ACM Transactions on Multimedia Computing, Communications, and Applications](/cms/asset/a23aab38-c0d1-4269-8824-642b15739370/3618076.cover.jpg)
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Check for updates
Author Tags
Qualifiers
- Research-article
Funding Sources
- National Natural Science Foundation of China
- Beijing Natural Science Foundation
- R&D Program of Beijing Municipal Education Commission
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 299Total Downloads
- Downloads (Last 12 months)299
- Downloads (Last 6 weeks)19
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in