Rethinking Omni Spatial-Frequency Representation for Efficient Face Super-Resolution.
- DOI
- 10.1109/tip.2026.3730840
- Published
- 2026
- Container
- IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/tip.2026.3730840,
title = {Rethinking Omni Spatial-Frequency Representation for Efficient Face Super-Resolution.},
author = {Xu Y and Zhao C and Chen Z and Zhang K and Yang J and Tai Y},
year = {2026},
journal = {IEEE transactions on image processing : a publication of the IEEE Signal Processing Society},
doi = {10.1109/tip.2026.3730840},
url = {https://doi.org/10.1109/tip.2026.3730840}
}RIS
TY - JOUR TI - Rethinking Omni Spatial-Frequency Representation for Efficient Face Super-Resolution. AU - Xu Y AU - Zhao C AU - Chen Z AU - Zhang K AU - Yang J AU - Tai Y PY - 2026 JO - IEEE transactions on image processing : a publication of the IEEE Signal Processing Society DO - 10.1109/tip.2026.3730840 UR - https://doi.org/10.1109/tip.2026.3730840 ER -
APA
Y, X., C, Z., Z, C., K, Z., J, Y., & Y, T. (2026). Rethinking Omni Spatial-Frequency Representation for Efficient Face Super-Resolution.. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. https://doi.org/10.1109/tip.2026.3730840
Source records
- pubmed · retrieved 2026-09-25T23:39:09.167Z