GAN-based anomaly detection: A review
X Xia, X Pan, N Li, X He, L Ma, X Zhang, N Ding - Neurocomputing, 2022 - Elsevier
Supervised learning algorithms have shown limited use in the field of anomaly detection due
to the unpredictability and difficulty in acquiring abnormal samples. In recent years …
to the unpredictability and difficulty in acquiring abnormal samples. In recent years …
Surface defect detection methods for industrial products: A review
Y Chen, Y Ding, F Zhao, E Zhang, Z Wu, L Shao - Applied Sciences, 2021 - mdpi.com
The comprehensive intelligent development of the manufacturing industry puts forward new
requirements for the quality inspection of industrial products. This paper summarizes the …
requirements for the quality inspection of industrial products. This paper summarizes the …
Openood: Benchmarking generalized out-of-distribution detection
J Yang, P Wang, D Zou, Z Zhou… - Advances in …, 2022 - proceedings.neurips.cc
Abstract Out-of-distribution (OOD) detection is vital to safety-critical machine learning
applications and has thus been extensively studied, with a plethora of methods developed in …
applications and has thus been extensively studied, with a plethora of methods developed in …
Simplenet: A simple network for image anomaly detection and localization
Z Liu, Y Zhou, Y Xu, Z Wang - Proceedings of the IEEE/CVF …, 2023 - openaccess.thecvf.com
We propose a simple and application-friendly network (called SimpleNet) for detecting and
localizing anomalies. SimpleNet consists of four components:(1) a pre-trained Feature …
localizing anomalies. SimpleNet consists of four components:(1) a pre-trained Feature …
Spot-the-difference self-supervised pre-training for anomaly detection and segmentation
Visual anomaly detection is commonly used in industrial quality inspection. In this paper, we
present a new dataset as well as a new self-supervised learning method for ImageNet pre …
present a new dataset as well as a new self-supervised learning method for ImageNet pre …
Winclip: Zero-/few-shot anomaly classification and segmentation
Visual anomaly classification and segmentation are vital for automating industrial quality
inspection. The focus of prior research in the field has been on training custom models for …
inspection. The focus of prior research in the field has been on training custom models for …
Multimodal industrial anomaly detection via hybrid fusion
Abstract 2D-based Industrial Anomaly Detection has been widely discussed, however,
multimodal industrial anomaly detection based on 3D point clouds and RGB images still has …
multimodal industrial anomaly detection based on 3D point clouds and RGB images still has …
Cfa: Coupled-hypersphere-based feature adaptation for target-oriented anomaly localization
For a long time, anomaly localization has been widely used in industries. Previous studies
focused on approximating the distribution of normal features without adaptation to a target …
focused on approximating the distribution of normal features without adaptation to a target …
MemSeg: A semi-supervised method for image surface defect detection using differences and commonalities
M Yang, P Wu, H Feng - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
High-accuracy and real-time semi-supervised image surface defect detection is extensively
needed in industrial scenarios. However, existing methods do not provide a good balance …
needed in industrial scenarios. However, existing methods do not provide a good balance …
Registration based few-shot anomaly detection
This paper considers few-shot anomaly detection (FSAD), a practical yet under-studied
setting for anomaly detection (AD), where only a limited number of normal images are …
setting for anomaly detection (AD), where only a limited number of normal images are …