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CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via
  Conditional Normalizing Flows

CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing Flows

27 July 2021
Denis A. Gudovskiy
Shun Ishizaka
Kazuki Kozuka
ArXivPDFHTML

Papers citing "CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing Flows"

37 / 37 papers shown
Title
PathoSCOPE: Few-Shot Pathology Detection via Self-Supervised Contrastive Learning and Pathology-Informed Synthetic Embeddings
Sinchee Chin
Yinuo Ma
Xiaochen Yang
Jing-Hao Xue
Wenming Yang
SSL
MedIm
55
0
0
23 May 2025
CostFilter-AD: Enhancing Anomaly Detection through Matching Cost Filtering
CostFilter-AD: Enhancing Anomaly Detection through Matching Cost Filtering
Zhe Zhang
Mingxiu Cai
Haoran Wang
Gaochang Wu
Tianyou Chai
Xiatian Zhu
89
0
0
02 May 2025
SAM-LAD: Segment Anything Model Meets Zero-Shot Logic Anomaly Detection
SAM-LAD: Segment Anything Model Meets Zero-Shot Logic Anomaly Detection
Yun Peng
Xiao Lin
Nachuan Ma
Jiayuan Du
Chuangwei Liu
Chengju Liu
Qi Chen
127
3
0
17 Feb 2025
SoftPatch+: Fully Unsupervised Anomaly Classification and Segmentation
SoftPatch+: Fully Unsupervised Anomaly Classification and Segmentation
Chengjie Wang
Xi Jiang
Bin-Bin Gao
Zhenye Gan
Yang Liu
Feng Zheng
Lizhuang Ma
UQCV
113
2
0
30 Dec 2024
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
Look Inside for More: Internal Spatial Modality Perception for 3D Anomaly Detection
Look Inside for More: Internal Spatial Modality Perception for 3D Anomaly Detection
Hanzhe Liang
Guoyang Xie
Chengbin Hou
Bingshu Wang
Can Gao
Jinbao Wang
3DPC
144
5
0
18 Dec 2024
View-Invariant Pixelwise Anomaly Detection in Multi-object Scenes with Adaptive View Synthesis
View-Invariant Pixelwise Anomaly Detection in Multi-object Scenes with Adaptive View Synthesis
Subin Varghese
Vedhus Hoskere
78
0
0
26 Jun 2024
End-to-End Augmentation Hyperparameter Tuning for Self-Supervised Anomaly Detection
End-to-End Augmentation Hyperparameter Tuning for Self-Supervised Anomaly Detection
Jaemin Yoo
Lingxiao Zhao
Leman Akoglu
71
4
0
21 Jun 2023
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
CutPaste: Self-Supervised Learning for Anomaly Detection and
  Localization
CutPaste: Self-Supervised Learning for Anomaly Detection and Localization
Chun-Liang Li
Kihyuk Sohn
Jinsung Yoon
Tomas Pfister
SSL
UQCV
76
775
0
08 Apr 2021
Multiresolution Knowledge Distillation for Anomaly Detection
Multiresolution Knowledge Distillation for Anomaly Detection
Mohammadreza Salehi
Niousha Sadjadi
Soroosh Baselizadeh
M. Rohban
Hamid R. Rabiee
113
440
0
22 Nov 2020
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
75
838
0
17 Nov 2020
A Unifying Review of Deep and Shallow Anomaly Detection
A Unifying Review of Deep and Shallow Anomaly Detection
Lukas Ruff
Jacob R. Kauffmann
Robert A. Vandermeulen
G. Montavon
Wojciech Samek
Marius Kloft
Thomas G. Dietterich
Klaus-Robert Muller
UQCV
104
797
0
24 Sep 2020
Same Same But DifferNet: Semi-Supervised Defect Detection with
  Normalizing Flows
Same Same But DifferNet: Semi-Supervised Defect Detection with Normalizing Flows
Marco Rudolph
Bastian Wandt
Bodo Rosenhahn
UQCV
39
328
0
28 Aug 2020
Encoding Structure-Texture Relation with P-Net for Anomaly Detection in
  Retinal Images
Encoding Structure-Texture Relation with P-Net for Anomaly Detection in Retinal Images
Kang Zhou
Yuting Xiao
Jianlong Yang
Jun Cheng
Wen Liu
Weixin Luo
Zaiwang Gu
Jiang-Dong Liu
Shenghua Gao
MedIm
69
118
0
09 Aug 2020
Patch SVDD: Patch-level SVDD for Anomaly Detection and Segmentation
Patch SVDD: Patch-level SVDD for Anomaly Detection and Segmentation
Jihun Yi
Sungroh Yoon
140
385
0
29 Jun 2020
Understanding Anomaly Detection with Deep Invertible Networks through
  Hierarchies of Distributions and Features
Understanding Anomaly Detection with Deep Invertible Networks through Hierarchies of Distributions and Features
R. Schirrmeister
Yuxuan Zhou
T. Ball
Dan Zhang
UQCV
54
88
0
18 Jun 2020
Why Normalizing Flows Fail to Detect Out-of-Distribution Data
Why Normalizing Flows Fail to Detect Out-of-Distribution Data
Polina Kirichenko
Pavel Izmailov
A. Wilson
OODD
83
275
0
15 Jun 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
120
239
0
28 May 2020
Sub-Image Anomaly Detection with Deep Pyramid Correspondences
Sub-Image Anomaly Detection with Deep Pyramid Correspondences
Niv Cohen
Yedid Hoshen
72
474
0
05 May 2020
Normalizing Flows for Probabilistic Modeling and Inference
Normalizing Flows for Probabilistic Modeling and Inference
George Papamakarios
Eric T. Nalisnick
Danilo Jimenez Rezende
S. Mohamed
Balaji Lakshminarayanan
TPM
AI4CE
202
1,691
0
05 Dec 2019
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
Guided Image Generation with Conditional Invertible Neural Networks
Guided Image Generation with Conditional Invertible Neural Networks
Lynton Ardizzone
Carsten T. Lüth
Jakob Kruse
Carsten Rother
Ullrich Kothe
DRL
83
294
0
04 Jul 2019
Searching for MobileNetV3
Searching for MobileNetV3
Andrew G. Howard
Mark Sandler
Grace Chu
Liang-Chieh Chen
Bo Chen
...
Yukun Zhu
Ruoming Pang
Vijay Vasudevan
Quoc V. Le
Hartwig Adam
340
6,772
0
06 May 2019
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
Analyzing Inverse Problems with Invertible Neural Networks
Analyzing Inverse Problems with Invertible Neural Networks
Lynton Ardizzone
Jakob Kruse
Sebastian J. Wirkert
D. Rahner
E. Pellegrini
R. Klessen
Lena Maier-Hein
Carsten Rother
Ullrich Kothe
53
490
0
14 Aug 2018
A Simple Unified Framework for Detecting Out-of-Distribution Samples and
  Adversarial Attacks
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks
Kimin Lee
Kibok Lee
Honglak Lee
Jinwoo Shin
OODD
179
2,049
0
10 Jul 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
q-Space Novelty Detection with Variational Autoencoders
q-Space Novelty Detection with Variational Autoencoders
A. Vasilev
Vladimir Golkov
Marc Meissner
I. Lipp
Eleonora Sgarlata
V. Tomassini
Derek K. Jones
Daniel Cremers
DRL
47
59
0
08 Jun 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
Attention Is All You Need
Attention Is All You Need
Ashish Vaswani
Noam M. Shazeer
Niki Parmar
Jakob Uszkoreit
Llion Jones
Aidan Gomez
Lukasz Kaiser
Illia Polosukhin
3DV
682
131,414
0
12 Jun 2017
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
Understanding the Effective Receptive Field in Deep Convolutional Neural
  Networks
Understanding the Effective Receptive Field in Deep Convolutional Neural Networks
Wenjie Luo
Yujia Li
R. Urtasun
R. Zemel
HAI
94
1,796
0
15 Jan 2017
Faster Eigenvector Computation via Shift-and-Invert Preconditioning
Faster Eigenvector Computation via Shift-and-Invert Preconditioning
Dan Garber
Laurent Dinh
Chi Jin
Jascha Narain Sohl-Dickstein
Samy Bengio
Praneeth Netrapalli
Aaron Sidford
263
78
0
26 May 2016
Wide Residual Networks
Wide Residual Networks
Sergey Zagoruyko
N. Komodakis
332
7,980
0
23 May 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
193,814
0
10 Dec 2015
Delving Deep into Rectifiers: Surpassing Human-Level Performance on
  ImageNet Classification
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
VLM
320
18,609
0
06 Feb 2015
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