RPCANet$^{++}$: Deep Interpretable Robust PCA for Sparse Object Segmentation.

Wu F, Dai Y, Zhang T, Ding Y, Yang J, Cheng MM, Peng Z

Open source

DOI
10.1109/tpami.2026.3697815
Published
2026 Oct
Container
IEEE transactions on pattern analysis and machine intelligence
Publisher
Not recorded
Open access
unknown

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BibTeX

@article{allodium:10.1109/tpami.2026.3697815,
  title = {RPCANet\$\textasciicircum{}\{++\}\$: Deep Interpretable Robust PCA for Sparse Object Segmentation.},
  author = {Wu F and Dai Y and Zhang T and Ding Y and Yang J and Cheng MM and Peng Z},
  year = {2026},
  journal = {IEEE transactions on pattern analysis and machine intelligence},
  doi = {10.1109/tpami.2026.3697815},
  url = {https://doi.org/10.1109/tpami.2026.3697815}
}

RIS

TY  - JOUR
TI  - RPCANet$^{++}$: Deep Interpretable Robust PCA for Sparse Object Segmentation.
AU  - Wu F
AU  - Dai Y
AU  - Zhang T
AU  - Ding Y
AU  - Yang J
AU  - Cheng MM
AU  - Peng Z
PY  - 2026
JO  - IEEE transactions on pattern analysis and machine intelligence
DO  - 10.1109/tpami.2026.3697815
UR  - https://doi.org/10.1109/tpami.2026.3697815
ER  -

APA

F, W., Y, D., T, Z., Y, D., J, Y., MM, C., & Z, P. (2026). RPCANet$^{++}$: Deep Interpretable Robust PCA for Sparse Object Segmentation.. IEEE transactions on pattern analysis and machine intelligence. https://doi.org/10.1109/tpami.2026.3697815

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