MFF-M3AD: A unified reconstruction method with multi-scale feature fusion for multi-category 3D anomaly detection

Hanzhe Liang, Chenxi Hu, Yejin Tang, Linlin Shen, Jinbao Wang, Can Gao

Open source

DOI
10.1016/j.neunet.2026.109131
Published
2026-11
Container
Neural Networks
Publisher
Elsevier BV
Open access
unknown

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BibTeX

@article{allodium:10.1016/j.neunet.2026.109131,
  title = {MFF-M3AD: A unified reconstruction method with multi-scale feature fusion for multi-category 3D anomaly detection},
  author = {Hanzhe Liang and Chenxi Hu and Yejin Tang and Linlin Shen and Jinbao Wang and Can Gao},
  year = {2026},
  journal = {Neural Networks},
  doi = {10.1016/j.neunet.2026.109131},
  url = {https://doi.org/10.1016/j.neunet.2026.109131}
}

RIS

TY  - JOUR
TI  - MFF-M3AD: A unified reconstruction method with multi-scale feature fusion for multi-category 3D anomaly detection
AU  - Hanzhe Liang
AU  - Chenxi Hu
AU  - Yejin Tang
AU  - Linlin Shen
AU  - Jinbao Wang
AU  - Can Gao
PY  - 2026
JO  - Neural Networks
DO  - 10.1016/j.neunet.2026.109131
UR  - https://doi.org/10.1016/j.neunet.2026.109131
ER  - 

APA

Liang, H., Hu, C., Tang, Y., Shen, L., Wang, J., & Gao, C. (2026). MFF-M3AD: A unified reconstruction method with multi-scale feature fusion for multi-category 3D anomaly detection. Neural Networks. https://doi.org/10.1016/j.neunet.2026.109131

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