Cover Image

Self-Supervised Training with Autoencoders for Visual Anomaly Detection

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Bauer, Alexander, Nakajima, Shinichi, Müller, Klaus-Robert
Format:	Preprint
Published:	2022
Subjects:	Computer Vision and Pattern Recognition Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Noise & pattern: identity-anchored Tikhonov regularization for robust structural anomaly detection
by: Bauer, Alexander, et al.
Published: (2025)

Hyperspectral Anomaly Detection with Self-Supervised Anomaly Prior
by: Liu, Yidan, et al.
Published: (2024)

Self-Tuning Self-Supervised Image Anomaly Detection
by: Yoo, Jaemin, et al.
Published: (2023)

Self-Supervised Siamese Autoencoders
by: Baier, Friederike, et al.
Published: (2023)

Self-Supervised Iterative Refinement for Anomaly Detection in Industrial Quality Control
by: Aqeel, Muhammad, et al.
Published: (2024)

Rethinking Autoencoders for Medical Anomaly Detection from A Theoretical Perspective
by: Cai, Yu, et al.
Published: (2024)

Supervised Anomaly Detection for Complex Industrial Images
by: Baitieva, Aimira, et al.
Published: (2024)

Mixed Autoencoder for Self-supervised Visual Representation Learning
by: Chen, Kai, et al.
Published: (2023)

VAN-AD: Visual Masked Autoencoder with Normalizing Flow For Time Series Anomaly Detection
by: Chen, PengYu, et al.
Published: (2026)

Self-Supervised Anomaly Detection in the Wild: Favor Joint Embeddings Methods
by: Otero, Daniel, et al.
Published: (2024)

Exploiting Autoencoder's Weakness to Generate Pseudo Anomalies
by: Astrid, Marcella, et al.
Published: (2024)

Bayesian Autoencoder for Medical Anomaly Detection: Uncertainty-Aware Approach for Brain 2 MRI Analysis
by: Roy, Dip
Published: (2025)

Mixture Prototype Flow Matching for Open-Set Supervised Anomaly Detection
by: Wang, Fuyun, et al.
Published: (2026)

Towards Desiderata-Driven Design of Visual Counterfactual Explainers
by: Bender, Sidney, et al.
Published: (2025)

Explaining Bayesian Neural Networks
by: Bykov, Kirill, et al.
Published: (2021)

Structure is Supervision: Multiview Masked Autoencoders for Radiology
by: Laguna, Sonia, et al.
Published: (2025)

Reconstruction-Based Anomaly Localization via Knowledge-Informed Self-Training
by: Qian, Cheng, et al.
Published: (2024)

Robust Spectral Anomaly Detection in EELS Spectral Images via Three Dimensional Convolutional Variational Autoencoders
by: Sultanov, Seyfal, et al.
Published: (2024)

Self-Supervised Modality-Agnostic Pre-Training of Swin Transformers
by: Talasila, Abhiroop, et al.
Published: (2024)

Adaptive Deviation Learning for Visual Anomaly Detection with Data Contamination
by: Das, Anindya Sundar, et al.
Published: (2024)

Benchmarking Compact VLMs for Clip-Level Surveillance Anomaly Detection Under Weak Supervision
by: Borodin, Kirill, et al.
Published: (2026)

Wild Visual Navigation: Fast Traversability Learning via Pre-Trained Models and Online Self-Supervision
by: Mattamala, Matías, et al.
Published: (2024)

SupMAE: Supervised Masked Autoencoders Are Efficient Vision Learners
by: Liang, Feng, et al.
Published: (2022)

On-Device Continual Learning for Unsupervised Visual Anomaly Detection in Dynamic Manufacturing
by: Ren, Haoyu, et al.
Published: (2025)

From Pixels to Graphs: Deep Graph-Level Anomaly Detection on Dermoscopic Images
by: Xu, Dehn, et al.
Published: (2025)

Enhancing Semi-Supervised Multi-View Graph Convolutional Networks via Supervised Contrastive Learning and Self-Training
by: Xiao, Huaiyuan, et al.
Published: (2025)

FUN-AD: Fully Unsupervised Learning for Anomaly Detection with Noisy Training Data
by: Im, Jiin, et al.
Published: (2024)

An Empirical Study of Accuracy-Robustness Tradeoff and Training Efficiency in Self-Supervised Learning
by: Ghofrani, Fatemeh, et al.
Published: (2025)

Self-Supervised Detection of Perfect and Partial Input-Dependent Symmetries
by: Urbano, Alonso, et al.
Published: (2023)

S-JEA: Stacked Joint Embedding Architectures for Self-Supervised Visual Representation Learning
by: Manová, Alžběta, et al.
Published: (2023)

Extracting Symbolic Sequences from Visual Representations via Self-Supervised Learning
by: Pozos, Victor Sebastian Martinez, et al.
Published: (2025)

SubspaceAD: Training-Free Few-Shot Anomaly Detection via Subspace Modeling
by: Lendering, Camile, et al.
Published: (2026)

ProFeAT: Projected Feature Adversarial Training for Self-Supervised Learning of Robust Representations
by: Addepalli, Sravanti, et al.
Published: (2024)

CADet: Fully Self-Supervised Out-Of-Distribution Detection With Contrastive Learning
by: Guille-Escuret, Charles, et al.
Published: (2022)

An AI System for Continuous Knee Osteoarthritis Severity Grading Using Self-Supervised Anomaly Detection with Limited Data
by: Belton, Niamh, et al.
Published: (2024)

Weakly-Supervised Anomaly Detection in Surveillance Videos Based on Two-Stream I3D Convolution Network
by: Nejad, Sareh Soltani, et al.
Published: (2024)

Sidewalk Hazard Detection Using Variational Autoencoder and One-Class SVM
by: Guzman, Edgar, et al.
Published: (2024)

Masked Autoencoders for Ultrasound Signals: Robust Representation Learning for Downstream Applications
by: Roßteutscher, Immanuel, et al.
Published: (2025)

On the Problem of Consistent Anomalies in Zero-Shot Anomaly Detection
by: Le-Gia, Tai
Published: (2025)

Intelligent Anomaly Detection for Lane Rendering Using Transformer with Self-Supervised Pre-Training and Customized Fine-Tuning
by: Dong, Yongqi, et al.
Published: (2023)