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Real-IAD D3: A Real-World 2D/Pseudo-3D/3D Dataset for Industrial Anomaly Detection

Real-IAD D3: A Real-World 2D/Pseudo-3D/3D Dataset for Industrial Anomaly Detection

19 April 2025
Wenbing Zhu
Lidong Wang
Ziqing Zhou
Chengjie Wang
Yurui Pan
Ruoyi Zhang
Zhuhao Chen
Linjie Cheng
Bin-Bin Gao
Jiangning Zhang
Zhenye Gan
Yun Wang
Yulong Chen
Shuguang Qian
M. Chi
Bo Peng
Lizhuang Ma
ArXiv (abs)PDFHTML

Papers citing "Real-IAD D3: A Real-World 2D/Pseudo-3D/3D Dataset for Industrial Anomaly Detection"

10 / 10 papers shown
Title
Visual Anomaly Detection under Complex View-Illumination Interplay: A Large-Scale Benchmark
Visual Anomaly Detection under Complex View-Illumination Interplay: A Large-Scale Benchmark
Yunkang Cao
Yuqi Cheng
Xiaohao Xu
Yiheng Zhang
Yihan Sun
Yuxiang Tan
Yuxin Zhang
Xiaonan Huang
Nong Sang
62
0
0
16 May 2025
Real-IAD: A Real-World Multi-View Dataset for Benchmarking Versatile
  Industrial Anomaly Detection
Real-IAD: A Real-World Multi-View Dataset for Benchmarking Versatile Industrial Anomaly Detection
Chengjie Wang
Wenbing Zhu
Bin-Bin Gao
Zhenye Gan
Jianning Zhang
Zhihao Gu
Shuguang Qian
Mingang Chen
Lizhuang Ma
106
55
0
19 Mar 2024
Learning Unified Reference Representation for Unsupervised Multi-class
  Anomaly Detection
Learning Unified Reference Representation for Unsupervised Multi-class Anomaly Detection
Liren He
Zhengkai Jiang
Jinlong Peng
Liang Liu
Qiangang Du
Xiaobin Hu
Wenbing Zhu
Mingmin Chi
Yabiao Wang
Chengjie Wang
59
11
0
18 Mar 2024
A Unified Model for Multi-class Anomaly Detection
A Unified Model for Multi-class Anomaly Detection
Zhiyuan You
Lei Cui
Yujun Shen
Kai Yang
Xin Lu
Yu Zheng
Xinyi Le
72
226
0
08 Jun 2022
Back to the Feature: Classical 3D Features are (Almost) All You Need for
  3D Anomaly Detection
Back to the Feature: Classical 3D Features are (Almost) All You Need for 3D Anomaly Detection
Eliahu Horwitz
Yedid Hoshen
110
54
0
10 Mar 2022
Anomaly Detection in 3D Point Clouds using Deep Geometric Descriptors
Anomaly Detection in 3D Point Clouds using Deep Geometric Descriptors
Paul Bergmann
David Sattlegger
3DPC
73
59
0
23 Feb 2022
Towards Total Recall in Industrial Anomaly Detection
Towards Total Recall in Industrial Anomaly Detection
Karsten Roth
Latha Pemula
J. Zepeda
Bernhard Schölkopf
Thomas Brox
Peter V. Gehler
UQCV
88
919
0
15 Jun 2021
PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and
  Localization
PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization
Thomas Defard
Aleksandr Setkov
Angélique Loesch
Romaric Audigier
UQCV
79
848
0
17 Nov 2020
Modeling the Distribution of Normal Data in Pre-Trained Deep Features
  for Anomaly Detection
Modeling the Distribution of Normal Data in Pre-Trained Deep Features for Anomaly Detection
Oliver Rippel
Patrick Mertens
Dorit Merhof
133
240
0
28 May 2020
Uninformed Students: Student-Teacher Anomaly Detection with
  Discriminative Latent Embeddings
Uninformed Students: Student-Teacher Anomaly Detection with Discriminative Latent Embeddings
Paul Bergmann
Michael Fauser
David Sattlegger
C. Steger
84
666
0
06 Nov 2019
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