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Few-Shot Anomaly Detection with Adversarial Loss for Robust Feature
  Representations

Few-Shot Anomaly Detection with Adversarial Loss for Robust Feature Representations

4 December 2023
Jae Young Lee
Won-Sang Lee
Jae-Young Choi
Yongkwi Lee
Young Seog Yoon
    AAML
ArXivPDFHTML

Papers citing "Few-Shot Anomaly Detection with Adversarial Loss for Robust Feature Representations"

3 / 3 papers shown
Title
PA-CLIP: Enhancing Zero-Shot Anomaly Detection through Pseudo-Anomaly Awareness
Yurui Pan
Lidong Wang
Yuchao Chen
Wenbing Zhu
Bo Peng
M. Chi
69
0
0
03 Mar 2025
Few-Shot Anomaly Detection via Category-Agnostic Registration Learning
Few-Shot Anomaly Detection via Category-Agnostic Registration Learning
Chaoqin Huang
Haoyan Guan
Aofan Jiang
Yanfeng Wang
Michael W. Spratling
Xinchao Wang
Ya Zhang
59
0
0
13 Jun 2024
Domain-Adversarial Training of Neural Networks
Domain-Adversarial Training of Neural Networks
Yaroslav Ganin
E. Ustinova
Hana Ajakan
Pascal Germain
Hugo Larochelle
François Laviolette
M. Marchand
Victor Lempitsky
GAN
OOD
177
9,327
0
28 May 2015
1