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

Fengyi Wu, Yimian Dai, Tianfang Zhang, Yixuan Ding, Jian Yang, Ming-Ming Cheng, Zhenming Peng

Open source

DOI
10.1109/tpami.2026.3697815
Published
2026-10
Container
IEEE Transactions on Pattern Analysis and Machine Intelligence
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Open access
unknown

Credibility signals

uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

Cite this work

BibTeX

@article{allodium:10.1109/tpami.2026.3697815,
  title = {RPCANet\$\textasciicircum{}\{++\}\$: Deep Interpretable Robust PCA for Sparse Object Segmentation},
  author = {Fengyi Wu and Yimian Dai and Tianfang Zhang and Yixuan Ding and Jian Yang and Ming-Ming Cheng and Zhenming Peng},
  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  - Fengyi Wu
AU  - Yimian Dai
AU  - Tianfang Zhang
AU  - Yixuan Ding
AU  - Jian Yang
AU  - Ming-Ming Cheng
AU  - Zhenming Peng
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

Wu, F., Dai, Y., Zhang, T., Ding, Y., Yang, J., Cheng, M., & Peng, Z. (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

Source records