Fetching the paper…
Reading the bibliography…
Recent advances in diffusion models have spurred research into their application for Reconstruction-based unsupervised anomaly detection.
Auto-encoding variational bayes
Diederik P Kingma · 2013
Earlier work this paper cites.
Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Unsupervised anomaly detection with generative adversarial networks to guide marker discovery
Thomas Schlegl, Philipp Seeböck, Sebastian M Waldstein, Ursula Schmidt-Erfurth, and Georg Langs · 2017
Earlier work this paper cites.
The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
Earlier work this paper cites.
Mvtec ad–a comprehensive real-world dataset for unsupervised anomaly detection
Paul Bergmann, Michael Fauser, David Sattlegger, and Carsten Steger · 2019
Earlier work this paper cites.
Ocgan: One-class novelty detection using gans with constrained latent representations
Pramuditha Perera, Ramesh Nallapati, and Bing Xiang · 2019
Earlier work this paper cites.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Earlier work this paper cites.
Towards visually explaining variational autoencoders
Wenqian Liu, Runze Li, Meng Zheng, Srikrishna Karanam, Ziyan Wu, Bir Bhanu, Richard J Radke, and Octavia Camps · 2020
Earlier work this paper cites.
Self-trained deep ordinal regression for end-to-end video anomaly detection
Guansong Pang, Cheng Yan, Chunhua Shen, Anton van den Hengel, and Xiao Bai · 2020
Earlier work this paper cites.
Padim: a patch distribution modeling framework for anomaly detection and localization
Thomas Defard, Aleksandr Setkov, Angelique Loesch, and Romaric Audigier · 2021
Earlier work this paper cites.
Deep learning-based defect detection of metal parts: evaluating current methods in complex conditions
Stepan Jezek, Martin Jonak, Radim Burget, Pavel Dvorak, and Milos Skotak · 2021
Earlier work this paper cites.
Cutpaste: Self-supervised learning for anomaly detection and localization
Chun-Liang Li, Kihyuk Sohn, Jinsung Yoon, and Tomas Pfister · 2021
Cited alongside, same era.
Improved denoising diffusion probabilistic models
Alexander Quinn Nichol and Prafulla Dhariwal · 2021
Cited alongside, same era.
Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2021
Cited alongside, same era.
Learning semantic context from normal samples for unsupervised anomaly detection
Xudong Yan, Huaidong Zhang, Xuemiao Xu, Xiaowei Hu, and Pheng-Ann Heng · 2021
Cited alongside, same era.
Draem-a discriminatively trained reconstruction embedding for surface anomaly detection
Vitjan Zavrtanik, Matej Kristan, and Danijel Skočaj · 2021
Cited alongside, same era.
Anomaly detection via reverse distillation from one-class embedding
Hanqiu Deng and Xingyu Li · 2022
A unified model for multi-class anomaly detection
Zhiyuan You, Lei Cui, Yujun Shen, Kai Yang, Xin Lu, Yu Zheng, and Xinyi Le · 2022
Later among the works it cites.
Dsr–a dual subspace re-projection network for surface anomaly detection
Vitjan Zavrtanik, Matej Kristan, and Danijel Skočaj · 2022
Later among the works it cites.
Spot-the-difference self-supervised pre-training for anomaly detection and segmentation
Yang Zou, Jongheon Jeong, Latha Pemula, Dongqing Zhang, and Onkar Dabeer · 2022
Later among the works it cites.
Simplenet: A simple network for image anomaly detection and localization
Zhikang Liu, Yiming Zhou, Yuansheng Xu, and Zilei Wang · 2023
Later among the works it cites.
Feature prediction diffusion model for video anomaly detection
Cheng Yan, Shiyu Zhang, Yang Liu, Guansong Pang, and Wenjun Wang · 2023
Later among the works it cites.
Transfusion–a transparency-based diffusion model for anomaly detection
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Cflow-ad: Real-time unsupervised anomaly detection with localization via conditional normalizing flows
Denis Gudovskiy, Shun Ishizaka, and Kazuki Kozuka · 2022
Cited alongside, same era.
High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Cited alongside, same era.
Towards total recall in industrial anomaly detection
Karsten Roth, Latha Pemula, Joaquin Zepeda, Bernhard Schölkopf, Thomas Brox, and Peter Gehler · 2022
Cited alongside, same era.
Fully convolutional cross-scale-flows for image-based defect detection
Marco Rudolph, Tom Wehrbein, Bodo Rosenhahn, and Bastian Wandt · 2022
Cited alongside, same era.
Natural synthetic anomalies for self-supervised anomaly detection and localization
Hannah M Schlüter, Jeremy Tan, Benjamin Hou, and Bernhard Kainz · 2022
Cited alongside, same era.
Constrained unsupervised anomaly segmentation
Julio Silva-Rodríguez, Valery Naranjo, and Jose Dolz · 2022
Cited alongside, same era.
Matic Fučka, Vitjan Zavrtanik, and Danijel Skočaj · 2024
Later among the works it cites.
Recontrast: Domain-specific anomaly detection via contrastive reconstruction
Jia Guo, Lize Jia, Weihang Zhang, Huiqi Li, et al · 2024
Later among the works it cites.
Hyperbolic anomaly detection
Huimin Li, Zhentao Chen, Yunhao Xu, and Junlin Hu · 2024
Later among the works it cites.
Moead: A parameter-efficient model for multi-class anomaly detection
Shiyuan Meng, Wenchao Meng, Qihang Zhou, Shizhong Li, Weiye Hou, and Shibo He · 2024
Later among the works it cites.
Real-iad: A real-world multi-view dataset for benchmarking versatile industrial anomaly detection
Chengjie Wang, Wenbing Zhu, Bin-Bin Gao, Zhenye Gan, Jiangning Zhang, Zhihao Gu, Shuguang Qian, Mingang Chen, and Lizhuang Ma · 2024
Later among the works it cites.
Glad: Towards better reconstruction with global and local adaptive diffusion models for unsupervised anomaly detection
Hang Yao, Ming Liu, Haolin Wang, Zhicun Yin, Zifei Yan, Xiaopeng Hong, and Wangmeng Zuo · 2024
Later among the works it cites.
Vision mamba: Efficient visual representation learning with bidirectional state space model
Lianghui Zhu, Bencheng Liao, Qian Zhang, Xinlong Wang, Wenyu Liu, and Xinggang Wang · 2024
Later among the works it cites.