Cover Image

Robust Anomaly Detection in Industrial Environments via Meta-Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Aqeel, Muhammad, Sharifi, Shakiba, Cristani, Marco, Setti, Francesco
Format:	Preprint
Published:	2025
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

Meta Learning-Driven Iterative Refinement for Robust Anomaly Detection in Industrial Inspection
by: Aqeel, Muhammad, et al.
Published: (2025)

Towards Real Unsupervised Anomaly Detection Via Confident Meta-Learning
by: Aqeel, Muhammad, et al.
Published: (2025)

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

A Contrastive Learning-Guided Confident Meta-learning for Zero Shot Anomaly Detection
by: Aqeel, Muhammad, et al.
Published: (2025)

Anomaly-Aware Vision-Language Adapters for Zero-Shot Anomaly Detection
by: Aqeel, Muhammad, et al.
Published: (2026)

Diffusion-based Image Generation for In-distribution Data Augmentation in Surface Defect Detection
by: Capogrosso, Luigi, et al.
Published: (2024)

Diffusion-Based Data Augmentation for Medical Image Segmentation
by: Nazir, Maham, et al.
Published: (2025)

Leveraging Latent Diffusion Models for Training-Free In-Distribution Data Augmentation for Surface Defect Detection
by: Girella, Federico, et al.
Published: (2024)

ExDD: Explicit Dual Distribution Learning for Surface Defect Detection via Diffusion Synthesis
by: Aqeel, Muhammad, et al.
Published: (2025)

RoadFusion: Latent Diffusion Model for Pavement Defect Detection
by: Aqeel, Muhammad, et al.
Published: (2025)

Adversarially Robust Industrial Anomaly Detection Through Diffusion Model
by: Cao, Yuanpu, et al.
Published: (2024)

Enhancing Split Computing and Early Exit Applications through Predefined Sparsity
by: Capogrosso, Luigi, et al.
Published: (2024)

Is SAM3 ready for pathology segmentation?
by: Kong, Qiuyu, et al.
Published: (2026)

Tailored Transformation Invariance for Industrial Anomaly Detection
by: Schönfeld, Mariette, et al.
Published: (2025)

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

Multimodal Abstractive Summarization of Instructional Videos with Vision-Language Models
by: Nazir, Maham, et al.
Published: (2026)

Well Googled is Half Done: Multimodal Forecasting of New Fashion Product Sales with Image-based Google Trends
by: Skenderi, Geri, et al.
Published: (2021)

MDiFF: Exploiting Multimodal Score-based Diffusion Models for New Fashion Product Performance Forecasting
by: Avogaro, Andrea, et al.
Published: (2024)

Dif4FF: Leveraging Multimodal Diffusion Models and Graph Neural Networks for Accurate New Fashion Product Performance Forecasting
by: Avogaro, Andrea, et al.
Published: (2024)

Collaborative Learning of Anomalies with Privacy (CLAP) for Unsupervised Video Anomaly Detection: A New Baseline
by: Al-lahham, Anas, et al.
Published: (2024)

Revisiting Deep Feature Reconstruction for Logical and Structural Industrial Anomaly Detection
by: Patra, Sukanya, et al.
Published: (2024)

Multi-Flow: Multi-View-Enriched Normalizing Flows for Industrial Anomaly Detection
by: Kruse, Mathis, et al.
Published: (2025)

Rethinking Continual Anomaly Detection on the Edge: Benchmarking Under Realistic Industrial Conditions
by: Weatherly, Chad, et al.
Published: (2026)

New Fashion Products Performance Forecasting: A Survey on Evolutions, Models and Emerging Trends
by: Avogaro, Andrea, et al.
Published: (2025)

PUAD: Frustratingly Simple Method for Robust Anomaly Detection
by: Sugawara, Shota, et al.
Published: (2024)

Multi-Camera Industrial Open-Set Person Re-Identification and Tracking
by: Cunico, Federico, et al.
Published: (2024)

PatchGuard: Adversarially Robust Anomaly Detection and Localization through Vision Transformers and Pseudo Anomalies
by: Nafez, Mojtaba, et al.
Published: (2025)

Multi-feature Reconstruction Network using Crossed-mask Restoration for Unsupervised Industrial Anomaly Detection
by: Wang, Junpu, et al.
Published: (2024)

SplatPose & Detect: Pose-Agnostic 3D Anomaly Detection
by: Kruse, Mathis, et al.
Published: (2024)

Efficient Training of Deep Networks using Guided Spectral Data Selection: A Step Toward Learning What You Need
by: Sharifi, Mohammadreza, et al.
Published: (2025)

MindfulLIME: A Stable Solution for Explanations of Machine Learning Models with Enhanced Localization Precision -- A Medical Image Case Study
by: Rahimiaghdam, Shakiba, et al.
Published: (2025)

MTL-Split: Multi-Task Learning for Edge Devices using Split Computing
by: Capogrosso, Luigi, et al.
Published: (2024)

SITUATE: Indoor Human Trajectory Prediction through Geometric Features and Self-Supervised Vision Representation
by: Capogrosso, Luigi, et al.
Published: (2024)

Latent Space Synergy: Text-Guided Data Augmentation for Direct Diffusion Biomedical Segmentation
by: Aqeel, Muhammad, et al.
Published: (2025)

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

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

Vision Foundation Model Embedding-Based Semantic Anomaly Detection
by: Ronecker, Max Peter, et al.
Published: (2025)

Unveiling the Anomalies in an Ever-Changing World: A Benchmark for Pixel-Level Anomaly Detection in Continual Learning
by: Bugarin, Nikola, et al.
Published: (2024)

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

Out-of-Distribution Detection with Relative Angles
by: Demirel, Berker, et al.
Published: (2024)