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G2D: Generate to Detect Anomaly

G2D: Generate to Detect Anomaly

20 June 2020
M. PourReza
Bahram Mohammadi
Mostafa Khaki
Samir Bouindour
H. Snoussi
Mohammad Sabokrou
ArXivPDFHTML

Papers citing "G2D: Generate to Detect Anomaly"

19 / 19 papers shown
Title
Deep Learning for Video Anomaly Detection: A Review
Deep Learning for Video Anomaly Detection: A Review
Peng Wu
Chengyu Pan
Yuting Yan
Guansong Pang
Peng Wang
Yanning Zhang
VLM
AI4TS
50
6
0
09 Sep 2024
Enhancing Anomaly Detection Generalization through Knowledge Exposure:
  The Dual Effects of Augmentation
Enhancing Anomaly Detection Generalization through Knowledge Exposure: The Dual Effects of Augmentation
Mohammad Akhavan Anvari
Rojina Kashefi
Vahid Reza Khazaie
Mohammad Khalooei
Mohammad Sabokrou
48
0
0
15 Jun 2024
A Comprehensive Survey on Machine Learning Driven Material Defect Detection
A Comprehensive Survey on Machine Learning Driven Material Defect Detection
Jun Bai
Di Wu
T. Shelley
Peter Schubel
David Twine
John Russell
Xuesen Zeng
J. Zhang
75
6
0
12 Jun 2024
Contextual Affinity Distillation for Image Anomaly Detection
Contextual Affinity Distillation for Image Anomaly Detection
Jie Zhang
Masanori Suganuma
Takayuki Okatani
42
14
0
06 Jul 2023
MixedTeacher : Knowledge Distillation for fast inference textural
  anomaly detection
MixedTeacher : Knowledge Distillation for fast inference textural anomaly detection
Simon Thomine
H. Snoussi
Mahmoud Soua
33
5
0
16 Jun 2023
FABLE : Fabric Anomaly Detection Automation Process
FABLE : Fabric Anomaly Detection Automation Process
Simon Thomine
H. Snoussi
Mahmoud Soua
27
5
0
16 Jun 2023
Anomaly Detection under Distribution Shift
Anomaly Detection under Distribution Shift
T. Cao
Jiawen Zhu
Guansong Pang
48
26
0
24 Mar 2023
PseudoBound: Limiting the anomaly reconstruction capability of one-class
  classifiers using pseudo anomalies
PseudoBound: Limiting the anomaly reconstruction capability of one-class classifiers using pseudo anomalies
Marcella Astrid
M. Zaheer
Seung-Ik Lee
26
17
0
19 Mar 2023
Whole-slide-imaging Cancer Metastases Detection and Localization with
  Limited Tumorous Data
Whole-slide-imaging Cancer Metastases Detection and Localization with Limited Tumorous Data
Yinsheng He
Xingyu Li
MedIm
25
2
0
18 Mar 2023
Dissolving Is Amplifying: Towards Fine-Grained Anomaly Detection
Dissolving Is Amplifying: Towards Fine-Grained Anomaly Detection
Jian Shi
Pengyi Zhang
Ni Zhang
Hakim Ghazzai
Y. Massoud
MedIm
43
6
0
28 Feb 2023
Robust One-Class Classification with Signed Distance Function using
  1-Lipschitz Neural Networks
Robust One-Class Classification with Signed Distance Function using 1-Lipschitz Neural Networks
Louis Bethune
Paul Novello
Thibaut Boissin
Guillaume Coiffier
M. Serrurier
Quentin Vincenot
Andres Troya-Galvis
36
8
0
26 Jan 2023
Teacher-Student Network for 3D Point Cloud Anomaly Detection with Few
  Normal Samples
Teacher-Student Network for 3D Point Cloud Anomaly Detection with Few Normal Samples
Jianjian Qin
Chunzhi Gu
Junzhou Yu
Chaoxi Zhang
3DPC
29
12
0
31 Oct 2022
Connective Reconstruction-based Novelty Detection
Connective Reconstruction-based Novelty Detection
Seyyed Morteza Hashemi
Parvaneh Aliniya
Parvin Razzaghi
OODD
22
0
0
25 Oct 2022
Augment to Detect Anomalies with Continuous Labelling
Augment to Detect Anomalies with Continuous Labelling
Vahid Reza Khazaie
A. Wong
Y. Mohsenzadeh
25
1
0
03 Jul 2022
Anomaly Detection with Adversarially Learned Perturbations of Latent
  Space
Anomaly Detection with Adversarially Learned Perturbations of Latent Space
Vahid Reza Khazaie
A. Wong
John Taylor Jewell
Y. Mohsenzadeh
AAML
42
3
0
03 Jul 2022
Anomaly Detection via Reverse Distillation from One-Class Embedding
Anomaly Detection via Reverse Distillation from One-Class Embedding
Hanqiu Deng
Xingyu Li
UQCV
123
450
0
26 Jan 2022
FROB: Few-shot ROBust Model for Classification and Out-of-Distribution
  Detection
FROB: Few-shot ROBust Model for Classification and Out-of-Distribution Detection
Nikolaos Dionelis
Mehrdad Yaghoobi
Sotirios A. Tsaftaris
OODD
19
4
0
30 Nov 2021
OMASGAN: Out-of-Distribution Minimum Anomaly Score GAN for Sample
  Generation on the Boundary
OMASGAN: Out-of-Distribution Minimum Anomaly Score GAN for Sample Generation on the Boundary
Nikolaos Dionelis
Mehrdad Yaghoobi
Sotirios A. Tsaftaris
OODD
25
6
0
28 Oct 2021
Learning Not to Reconstruct Anomalies
Learning Not to Reconstruct Anomalies
Marcella Astrid
M. Zaheer
Jae-Yeong Lee
Seung-Ik Lee
15
46
0
19 Oct 2021
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