Large-scale data for multiple-view stereopsis
- Submitting institution
-
Aston University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 23131523
- Type
- D - Journal article
- DOI
-
10.1007/s11263-016-0902-9
- Title of journal
- International Journal of Computer Vision
- Article number
- -
- First page
- 153
- Volume
- 120
- Issue
- 2
- ISSN
- 0920-5691
- Open access status
- Compliant
- Month of publication
- April
- Year of publication
- 2016
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
-
A - Aston Institute of Urban Technology and the Environment (ASTUTE)
- Citation count
- 36
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The article, a collaboration between Aston and DTU, Denmark, is a major benchmark for Multi-view stereo, one of the main Computer Vision tasks. It has been referenced by almost every paper published in the field since then and has led to several new methods that pushed the state of the art. The paper was presented at CVPR 2014 (http://www.pamitc.org/cvpr14/), one of the top conferences for Computer Vision.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
