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Anomaly localization by modeling perceptual features

Anomaly localization by modeling perceptual features

12 August 2020
David Dehaene
P. Eline
    DRL
ArXivPDFHTML

Papers citing "Anomaly localization by modeling perceptual features"

17 / 17 papers shown
Title
Kernel-Aware Graph Prompt Learning for Few-Shot Anomaly Detection
Kernel-Aware Graph Prompt Learning for Few-Shot Anomaly Detection
Fenfang Tao
G. Xie
Fang Zhao
Xiangbo Shu
92
2
0
23 Dec 2024
Dinomaly: The Less Is More Philosophy in Multi-Class Unsupervised Anomaly Detection
Dinomaly: The Less Is More Philosophy in Multi-Class Unsupervised Anomaly Detection
Jia Guo
Shuai Lu
Weihang Zhang
Huiqi Li
Huiqi Li
Hongen Liao
ViT
108
12
0
23 May 2024
DiffusionAD: Norm-guided One-step Denoising Diffusion for Anomaly Detection
DiffusionAD: Norm-guided One-step Denoising Diffusion for Anomaly Detection
Hui Zhang
Zheng Wang
Dan Zeng
Zuxuan Wu
Yu-Gang Jiang
DiffM
108
31
0
15 Mar 2023
Generative Adversarial Networks
Generative Adversarial Networks
Gilad Cohen
Raja Giryes
GAN
262
30,123
0
01 Mar 2022
Iterative energy-based projection on a normal data manifold for anomaly
  localization
Iterative energy-based projection on a normal data manifold for anomaly localization
David Dehaene
Oriel Frigo
Sébastien Combrexelle
P. Eline
32
145
0
10 Feb 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
72
662
0
06 Nov 2019
Diagnosing and Enhancing VAE Models
Diagnosing and Enhancing VAE Models
Bin Dai
David Wipf
DRL
59
380
0
14 Mar 2019
Are pre-trained CNNs good feature extractors for anomaly detection in
  surveillance videos?
Are pre-trained CNNs good feature extractors for anomaly detection in surveillance videos?
T. S. Nazaré
R. Mello
M. Ponti
44
45
0
20 Nov 2018
Do Deep Generative Models Know What They Don't Know?
Do Deep Generative Models Know What They Don't Know?
Eric T. Nalisnick
Akihiro Matsukawa
Yee Whye Teh
Dilan Görür
Balaji Lakshminarayanan
OOD
63
757
0
22 Oct 2018
Improving Unsupervised Defect Segmentation by Applying Structural
  Similarity to Autoencoders
Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoders
Paul Bergmann
Sindy Löwe
Michael Fauser
David Sattlegger
C. Steger
64
664
0
05 Jul 2018
Deep Autoencoding Models for Unsupervised Anomaly Segmentation in Brain
  MR Images
Deep Autoencoding Models for Unsupervised Anomaly Segmentation in Brain MR Images
Christoph Baur
Benedikt Wiestler
Shadi Albarqouni
Nassir Navab
UQCV
MedIm
52
442
0
12 Apr 2018
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
Richard Y. Zhang
Phillip Isola
Alexei A. Efros
Eli Shechtman
Oliver Wang
EGVM
363
11,784
0
11 Jan 2018
Unsupervised Anomaly Detection with Generative Adversarial Networks to
  Guide Marker Discovery
Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery
T. Schlegl
Philipp Seeböck
S. Waldstein
U. Schmidt-Erfurth
Georg Langs
MedIm
GAN
104
2,228
0
17 Mar 2017
NIPS 2016 Tutorial: Generative Adversarial Networks
NIPS 2016 Tutorial: Generative Adversarial Networks
Ian Goodfellow
GAN
163
1,723
0
31 Dec 2016
Deep-Anomaly: Fully Convolutional Neural Network for Fast Anomaly
  Detection in Crowded Scenes
Deep-Anomaly: Fully Convolutional Neural Network for Fast Anomaly Detection in Crowded Scenes
Mohammad Sabokrou
Mohsen Fayyaz
Mahmood Fathy
Zahra Moayed
Reinhard Klette
69
430
0
03 Sep 2016
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAtt
MDE
1.6K
100,330
0
04 Sep 2014
Auto-Encoding Variational Bayes
Auto-Encoding Variational Bayes
Diederik P. Kingma
Max Welling
BDL
443
16,940
0
20 Dec 2013
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