The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
Semi-coupled dictionary learning with applications to image super-resolution and photo-sketch synthesis
Abstract
In various computer vision applications, often we need to convert an image in one style into another style for better visualization, interpretation and recognition; for examples, up-convert a low resolution image to a high resolution one, and convert a face sketch into a photo for matching, etc. A semi-coupled dictionary learning (SCDL) model is proposed in this paper to solve such cross-style image synthesis problems. Under SCDL, a pair of dictionaries and a mapping function will be simultaneously learned. The dictionary pair can well characterize the structural domains of the two styles of images, while the mapping function can reveal the intrinsic relationship between the two styles' domains. In SCDL, the two dictionaries will not be fully coupled, and hence much flexibility can be given to the mapping function for an accurate conversion across styles. Moreover, clustering and image nonlocal redundancy are introduced to enhance the robustness of SCDL. The proposed SCDL model is applied to image super-resolution and photo-sketch synthesis, and the experimental results validated its generality and effectiveness in cross-style image synthesis.
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Cites
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Cited by
Shi, W., Caballero, J., Huszar, F., Totz, J., Aitken, A. P., Bishop, R., Rueckert, D., & Wang, Z. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.207 · Cited by 7,570
Second-Order Attention Network for Single Image Super-Resolution
Dai, T., Cai, J., Zhang, Y., Xia, S.-T., & Zhang, L. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.01132 · Cited by 2,010
Single-Image Super-Resolution: A Benchmark
Yang, C.-Y., Ma, C., & Yang, M.-H. (2014) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-10593-2_25 · Cited by 615
Image super-resolution: the techniques, applications, and future
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Self-citationAn Overview of Cross-Media Retrieval: Concepts, Methodologies, Benchmarks, and Challenges
Peng, Y., Huang, X., & Zhao, Y. (2018) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2017.2705068 · Cited by 341
Metadata
- Authors
- Wang, S., Zhang, L., Liang, Y., & Pan, Q.
- Venue
- 2012 IEEE Conference on Computer Vision and Pattern Recognition
- Publisher
- IEEE
- Published
- 2012-06
- Pages
- 2216-2223
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2120824855
- Cited by
- 532
- References
- 29
- FWCI
- 29.40
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Wang, S., Zhang, L., Liang, Y., & Pan, Q. (2012). Semi-coupled dictionary learning with applications to image super-resolution and photo-sketch synthesis. 2012 IEEE Conference on Computer Vision and Pattern Recognition. https://doi.org/10.1109/cvpr.2012.6247930
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