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}
}