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Inpainting Transformer for Anomaly Detection

Inpainting Transformer for Anomaly Detection

28 April 2021
Jonathan Pirnay
K. Chai
    ViT
ArXivPDFHTML

Papers citing "Inpainting Transformer for Anomaly Detection"

5 / 5 papers shown
Title
MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection
MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection
Haoyang He
Yuhu Bai
Jiangning Zhang
Qingdong He
Hongxu Chen
Zhenye Gan
Chengjie Wang
Xiangtai Li
Guanzhong Tian
Lei Xie
Mamba
42
32
0
09 Apr 2024
Long-Tailed Anomaly Detection with Learnable Class Names
Long-Tailed Anomaly Detection with Learnable Class Names
Chih-Hui Ho
Kuan-Chuan Peng
Nuno Vasconcelos
OODD
25
6
0
29 Mar 2024
Ano-SuPs: Multi-size anomaly detection for manufactured products by identifying suspected patches
Ano-SuPs: Multi-size anomaly detection for manufactured products by identifying suspected patches
Hao Xu
Juan Du
Andi Wang
YingCong Chen
19
1
0
20 Sep 2023
UniFormaly: Towards Task-Agnostic Unified Framework for Visual Anomaly
  Detection
UniFormaly: Towards Task-Agnostic Unified Framework for Visual Anomaly Detection
Yujin Lee
Harin Lim
Seoyoon Jang
H. Yoon
6
4
0
24 Jul 2023
Feasibility of Universal Anomaly Detection without Knowing the
  Abnormality in Medical Images
Feasibility of Universal Anomaly Detection without Knowing the Abnormality in Medical Images
C. Cui
Yaohong Wang
Shunxing Bao
Yucheng Tang
Ruining Deng
...
Qi Liu
Lori A. Coburn
K. Wilson
Bennett A. Landman
Yuankai Huo
OOD
18
0
0
03 Jul 2023
1