Deep learning for unsupervised anomaly localization in industrial images: A survey
X Tao, X Gong, X Zhang, S Yan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Currently, deep learning-based visual inspection has been highly successful with the help of
supervised learning methods. However, in real industrial scenarios, the scarcity of defect …
supervised learning methods. However, in real industrial scenarios, the scarcity of defect …
The MVTec anomaly detection dataset: a comprehensive real-world dataset for unsupervised anomaly detection
The detection of anomalous structures in natural image data is of utmost importance for
numerous tasks in the field of computer vision. The development of methods for …
numerous tasks in the field of computer vision. The development of methods for …
Efficientad: Accurate visual anomaly detection at millisecond-level latencies
Detecting anomalies in images is an important task, especially in real-time computer vision
applications. In this work, we focus on computational efficiency and propose a lightweight …
applications. In this work, we focus on computational efficiency and propose a lightweight …
Beyond dents and scratches: Logical constraints in unsupervised anomaly detection and localization
The unsupervised detection and localization of anomalies in natural images is an intriguing
and challenging problem. Anomalies manifest themselves in very different ways and an …
and challenging problem. Anomalies manifest themselves in very different ways and an …
Anomaly analysis in images and videos: A comprehensive review
Anomaly analysis is an important component of any surveillance system. In recent years, it
has drawn the attention of the computer vision and machine learning communities. In this …
has drawn the attention of the computer vision and machine learning communities. In this …
Anomaly detection in 3d point clouds using deep geometric descriptors
P Bergmann, D Sattlegger - Proceedings of the IEEE/CVF …, 2023 - openaccess.thecvf.com
We present a new method for the unsupervised detection of geometric anomalies in high-
resolution 3D point clouds. In particular, we propose an adaptation of the established …
resolution 3D point clouds. In particular, we propose an adaptation of the established …
A two-dimensional sparse matrix profile DenseNet for COVID-19 diagnosis using chest CT images
COVID-19 is a newly identified disease, which is very contagious and has been rapidly
spreading across different countries around the world, calling for rapid and accurate …
spreading across different countries around the world, calling for rapid and accurate …
Image anomaly detection using normal data only by latent space resampling
L Wang, D Zhang, J Guo, Y Han - Applied Sciences, 2020 - mdpi.com
Detecting image anomalies automatically in industrial scenarios can improve economic
efficiency, but the scarcity of anomalous samples increases the challenge of the task …
efficiency, but the scarcity of anomalous samples increases the challenge of the task …
Towards Scalable 3D Anomaly Detection and Localization: A Benchmark via 3D Anomaly Synthesis and A Self-Supervised Learning Network
W Li, X Xu, Y Gu, B Zheng, S Gao… - Proceedings of the …, 2024 - openaccess.thecvf.com
Recently 3D anomaly detection a crucial problem involving fine-grained geometry
discrimination is getting more attention. However the lack of abundant real 3D anomaly data …
discrimination is getting more attention. However the lack of abundant real 3D anomaly data …
图像异常检测研究现状综述
吕承侃， 沈飞， 张正涛， 张峰 - 自动化学报, 2022 - aas.net.cn
图像异常检测是计算机视觉领域的一个热门研究课题, 其目标是在不使用真实异常样本的情况下
, 利用现有的正常样本构建模型以检测可能出现的各种异常图像, 在工业外观缺陷检测 …
, 利用现有的正常样本构建模型以检测可能出现的各种异常图像, 在工业外观缺陷检测 …