Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression
- Submitting institution
-
Queen Mary University of London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 530
- Type
- E - Conference contribution
- DOI
-
10.1109/ICCV.2017.117
- Title of conference / published proceedings
- Proceedings of the IEEE International Conference on Computer Vision
- First page
- 1031
- Volume
- 2017-October
- Issue
- -
- ISSN
- 1550-5499
- Open access status
- Technical exception
- Month of publication
- December
- Year of publication
- 2017
- 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
-
3
- Research group(s)
-
-
- Citation count
- 84
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- "Software released on GitHub for this work has been widely used by the researchers/ practitioners, having attracted more than 4,100 stars (also featured on GitHub trending). See https://github.com/AaronJackson/vrn.
The demo released for the work has been used by thousands of users and has processed more than 1.3M faces since 09/2017. See https://cvl-demos.cs.nott.ac.uk/vrn/.
The work attracted wide publicity: it was featured on BBC news East Midlands. Among others, it was also featured on Verge, The Next Web, Seeker, DONG, Computerphile, The Register. See https://aaronsplace.co.uk/papers/jackson2017recon/index.html
Finally, the work appears on the first page of Google search for the term “3D Face Reconstruction”."
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -