MetaCAN: Improving Generalizability of Few-shot Anomaly Detection with Meta-learning.

Zhisheng Lv|Jianfeng Zhang|Songlei Jian|Chenlin Huang|Hongguang Zhang|Guansong Pang|Zhong Liu


Anthology ID:DBLP:conf/cikm/LvZJHZPL25
Volume:Proceedings of the 34th ACM International Conference on Information and Knowledge Management, CIKM 2025, Seoul, Republic of Korea, November 10-14, 2025
Year:2025
Venue:International Conference on Information and Knowledge Management (CIKM)
Publisher:ACM
Pages:2032-2041
URL:https://doi.org/10.1145/3746252.3761253
DOI:https://doi.org/10.1145/3746252.3761253
DBLP:conf/cikm/LvZJHZPL25
BibTeX:
@inproceedings{lv-2025-metacan, author = {Zhisheng Lv and Jianfeng Zhang and Songlei Jian and Chenlin Huang and Hongguang Zhang and Guansong Pang and Zhong Liu}, editor = {Meeyoung Cha and Carl Yang and Senjuti Basu Roy and Chanyoung Park and Zhenhui Jessie Li and Noseong Park and Carl Yang and Senjuti Basu Roy and Zhenhui Jessie Li and Jaap Kamps and Kijung Shin and Bryan Hooi and Lifang He}, title = {{MetaCAN: Improving Generalizability of Few-shot Anomaly Detection with Meta-learning}}, booktitle = {{Proceedings of the 34th ACM International Conference on Information and Knowledge Management, CIKM 2025, Seoul, Republic of Korea, November 10-14, 2025}}, pages = {2032--2041}, publisher = {ACM}, year = {2025}, url = {https://doi.org/10.1145/3746252.3761253}, doi = {https://doi.org/10.1145/3746252.3761253} }