Rethinking Omni Spatial-Frequency Representation for Efficient Face Super-Resolution.

Xu Y, Zhao C, Chen Z, Zhang K, Yang J, Tai Y

Open source

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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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

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