Depth Analogy: Data-Driven Approach for Single Image Depth Estimation Using Gradient Samples
- Submitting institution
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Queen Mary University of London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 526
- Type
- D - Journal article
- DOI
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10.1109/tip.2015.2495261
- Title of journal
- IEEE Transactions on Image Processing
- Article number
- -
- First page
- 5953
- Volume
- 24
- Issue
- 12
- ISSN
- 1057-7149
- Open access status
- Out of scope for open access requirements
- Month of publication
- October
- Year of publication
- 2015
- 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
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5
- Research group(s)
-
-
- Citation count
- 29
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The paper proposes a new gradient-domain approach for depth estimation from a single image. This is the outcome of the industrial collaboration with Samsung Electronics (South Korea, Jinsung Lee, jinsung7.lee@samsung.com) and the research is funded by Samsung Electronics (2D to Multiview Conversion System, 90,000,000 KRW (about 60,000GBP)).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -