What Does 2D Geometric Information Really Tell Us About 3D Face Shape?
- Submitting institution
-
University of York
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 62780527
- Type
- D - Journal article
- DOI
-
10.1007/s11263-019-01197-x
- Title of journal
- International Journal of Computer Vision
- Article number
- -
- First page
- 1455
- Volume
- 127
- Issue
- 10
- ISSN
- 0920-5691
- Open access status
- Compliant
- Month of publication
- July
- Year of publication
- 2019
- 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
-
1
- Research group(s)
-
-
- Citation count
- 1
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper builds on a highly cited ACCV 2016 workshop paper, an implementation of which was open sourced and widely used (>100 stars on github). The paper reveals a fundamental and surprising ambiguity in 3D face shape estimation with implications for 3D face modelling algorithms, face recognition and forensic face imaging. A tweet about the paper was viewed 10K times and a video viewed 2K times. Invited talks on this work have been given at UCSD, Bonn, Basel, a Dagstuhl seminar and as a keynote at an ICCV 2017 workshop.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
