Saliency propagation from simple to difficult
- Submitting institution
-
Birkbeck College
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 10
- Type
- E - Conference contribution
- DOI
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10.1109/CVPR.2015.7298868
- Title of conference / published proceedings
- 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
- First page
- 2531
- Volume
- -
- Issue
- -
- ISSN
- 1063-6919
- Open access status
- Out of scope for open access requirements
- Month of publication
- June
- Year of publication
- 2015
- URL
-
https://ieeexplore.ieee.org/document/7298868
- 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
-
6
- Research group(s)
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2 - Experimental Data Science
- Citation count
- 108
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper is the first to employ teaching to learn and learning to teach methods for saliency propagation. The paper resulted in multiple awards to Gong, including the Wu Wen-Jun AI Excellent Youth Scholar Award (Top AI award in China) and the Young Elite Scientists Sponsorship Program, China Association for Science and Technology (No: 2018QNRC001).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -