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MultiADS: Defect-aware Supervision for Multi-type Anomaly Detection and Segmentation in Zero-Shot Learning
v1v2 (latest)

MultiADS: Defect-aware Supervision for Multi-type Anomaly Detection and Segmentation in Zero-Shot Learning

9 April 2025
Ylli Sadikaj
Hongkuan Zhou
Lavdim Halilaj
Stefan Schmid
Steffen Staab
Claudia Plant
ArXiv (abs)PDFHTML

Papers citing "MultiADS: Defect-aware Supervision for Multi-type Anomaly Detection and Segmentation in Zero-Shot Learning"

5 / 5 papers shown
ProtoAnomalyNCD: Prototype Learning for Multi-class Novel Anomaly Discovery in Industrial Scenarios
ProtoAnomalyNCD: Prototype Learning for Multi-class Novel Anomaly Discovery in Industrial Scenarios
Botong Zhao
Qijun Shi
Shujing Lyu
Yue Lu
194
0
0
17 Nov 2025
UniADC: A Unified Framework for Anomaly Detection and Classification
UniADC: A Unified Framework for Anomaly Detection and Classification
Ximiao Zhang
Min Xu
Zheng Zhang
J. Hu
Xiuzhuang Zhou
153
0
0
10 Nov 2025
Image-Intrinsic Priors for Integrated Circuit Defect Detection and Novel Class Discovery via Self-Supervised Learning
Image-Intrinsic Priors for Integrated Circuit Defect Detection and Novel Class Discovery via Self-Supervised Learning
Botong.Zhao
Xubin.Wang
Shujing.Lyu
Yue.Lu
90
0
0
05 Nov 2025
Kernel-Aware Graph Prompt Learning for Few-Shot Anomaly Detection
Kernel-Aware Graph Prompt Learning for Few-Shot Anomaly DetectionAAAI Conference on Artificial Intelligence (AAAI), 2024
Fenfang Tao
G. Xie
Fang Zhao
Xiangbo Shu
291
15
0
23 Dec 2024
AnomalyDINO: Boosting Patch-based Few-shot Anomaly Detection with DINOv2
AnomalyDINO: Boosting Patch-based Few-shot Anomaly Detection with DINOv2IEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2024
Simon Damm
M. Laszkiewicz
Johannes Lederer
Asja Fischer
339
35
0
23 May 2024
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