MuSc-V2: Zero-Shot Multimodal Industrial Anomaly Classification and Segmentation With Mutual Scoring of Unlabeled Samples.
- DOI
- 10.1109/tpami.2026.3688174
- Published
- 2026 Sep
- Container
- IEEE transactions on pattern analysis and machine intelligence
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/tpami.2026.3688174,
title = {MuSc-V2: Zero-Shot Multimodal Industrial Anomaly Classification and Segmentation With Mutual Scoring of Unlabeled Samples.},
author = {Li X and Xue F and Zhou Y},
year = {2026},
journal = {IEEE transactions on pattern analysis and machine intelligence},
doi = {10.1109/tpami.2026.3688174},
url = {https://doi.org/10.1109/tpami.2026.3688174}
}RIS
TY - JOUR TI - MuSc-V2: Zero-Shot Multimodal Industrial Anomaly Classification and Segmentation With Mutual Scoring of Unlabeled Samples. AU - Li X AU - Xue F AU - Zhou Y PY - 2026 JO - IEEE transactions on pattern analysis and machine intelligence DO - 10.1109/tpami.2026.3688174 UR - https://doi.org/10.1109/tpami.2026.3688174 ER -
APA
X, L., F, X., & Y, Z. (2026). MuSc-V2: Zero-Shot Multimodal Industrial Anomaly Classification and Segmentation With Mutual Scoring of Unlabeled Samples.. IEEE transactions on pattern analysis and machine intelligence. https://doi.org/10.1109/tpami.2026.3688174
Source records
- pubmed · retrieved 2026-09-26T04:13:17.881Z