Copertina

AnomalyFactory: Regard Anomaly Generation as Unsupervised Anomaly Localization

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autore principale:	Zhao, Ying
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computer Vision and Pattern Recognition
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

AnomalyHybrid: A Domain-agnostic Generative Framework for General Anomaly Detection
di: Zhao, Ying
Pubblicazione: (2025)

Component-aware Unsupervised Logical Anomaly Generation for Industrial Anomaly Detection
di: Tong, Xuan, et al.
Pubblicazione: (2025)

Subspace-Guided Feature Reconstruction for Unsupervised Anomaly Localization
di: Hotta, Katsuya, et al.
Pubblicazione: (2023)

Fence off Anomaly Interference: Cross-Domain Distillation for Fully Unsupervised Anomaly Detection
di: Liu, Xinyue, et al.
Pubblicazione: (2025)

ASTER: Latent Pseudo-Anomaly Generation for Unsupervised Time-Series Anomaly Detection
di: Hermary, Romain, et al.
Pubblicazione: (2026)

GroundingAnomaly: Spatially-Grounded Diffusion for Few-Shot Anomaly Synthesis
di: Liu, Yishen, et al.
Pubblicazione: (2026)

PointCore: Efficient Unsupervised Point Cloud Anomaly Detector Using Local-Global Features
di: Zhao, Baozhu, et al.
Pubblicazione: (2024)

CSAD: Unsupervised Component Segmentation for Logical Anomaly Detection
di: Hsieh, Yu-Hsuan, et al.
Pubblicazione: (2024)

SoftPatch+: Fully Unsupervised Anomaly Classification and Segmentation
di: Wang, Chengjie, et al.
Pubblicazione: (2024)

Dual-Modeling Decouple Distillation for Unsupervised Anomaly Detection
di: Liu, Xinyue, et al.
Pubblicazione: (2024)

Exploring Multimodal Prompts For Unsupervised Continuous Anomaly Detection
di: Zhou, Mingle, et al.
Pubblicazione: (2026)

A Unified Anomaly Synthesis Strategy with Gradient Ascent for Industrial Anomaly Detection and Localization
di: Chen, Qiyu, et al.
Pubblicazione: (2024)

AnomalyDiffusion: Few-Shot Anomaly Image Generation with Diffusion Model
di: Hu, Teng, et al.
Pubblicazione: (2023)

Unsupervised Continual Anomaly Detection with Contrastively-learned Prompt
di: Liu, Jiaqi, et al.
Pubblicazione: (2024)

Weakly Supervised Video Anomaly Detection with Anomaly-Connected Components and Intention Reasoning
di: Wang, Yu, et al.
Pubblicazione: (2026)

Blind Localization and Clustering of Anomalies in Textures
di: Ardelean, Andrei-Timotei, et al.
Pubblicazione: (2024)

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

URA-Net: Uncertainty-Integrated Anomaly Perception and Restoration Attention Network for Unsupervised Anomaly Detection
di: Luo, Wei, et al.
Pubblicazione: (2026)

Learn Suspected Anomalies from Event Prompts for Video Anomaly Detection
di: Tao, Chenchen, et al.
Pubblicazione: (2024)

Unsupervised Anomaly Detection via Masked Diffusion Posterior Sampling
di: Wu, Di, et al.
Pubblicazione: (2024)

Vision-Language Models Assisted Unsupervised Video Anomaly Detection
di: Jiang, Yalong, et al.
Pubblicazione: (2024)

Context Enhancement with Reconstruction as Sequence for Unified Unsupervised Anomaly Detection
di: Yang, Hui-Yue, et al.
Pubblicazione: (2024)

Pyramid-based Mamba Multi-class Unsupervised Anomaly Detection
di: Iqbal, Nasar, et al.
Pubblicazione: (2025)

GLAD: Towards Better Reconstruction with Global and Local Adaptive Diffusion Models for Unsupervised Anomaly Detection
di: Yao, Hang, et al.
Pubblicazione: (2024)

Unseen Visual Anomaly Generation
di: Sun, Han, et al.
Pubblicazione: (2024)

AnomalyXFusion: Multi-modal Anomaly Synthesis with Diffusion
di: Hu, Jie, et al.
Pubblicazione: (2024)

ASBench: Image Anomalies Synthesis Benchmark for Anomaly Detection
di: Zhang, Qunyi, et al.
Pubblicazione: (2025)

MIRAGE: Model-agnostic Industrial Realistic Anomaly Generation and Evaluation for Visual Anomaly Detection
di: Hu, Jinwei, et al.
Pubblicazione: (2026)

Unsupervised Deep Generative Models for Anomaly Detection in Neuroimaging: A Systematic Scoping Review
di: Mahé, Youwan, et al.
Pubblicazione: (2025)

Few-Shot Anomaly-Driven Generation for Anomaly Classification and Segmentation
di: Gui, Guan, et al.
Pubblicazione: (2025)

Generate Aligned Anomaly: Region-Guided Few-Shot Anomaly Image-Mask Pair Synthesis for Industrial Inspection
di: Lu, Yilin, et al.
Pubblicazione: (2025)

When Unsupervised Domain Adaptation meets One-class Anomaly Detection: Addressing the Two-fold Unsupervised Curse by Leveraging Anomaly Scarcity
di: Mejri, Nesryne, et al.
Pubblicazione: (2025)

Anomaly Heterogeneity Learning for Open-set Supervised Anomaly Detection
di: Zhu, Jiawen, et al.
Pubblicazione: (2023)

Unsupervised Industrial Anomaly Detection via Pattern Generative and Contrastive Networks
di: Huang, Jianfeng, et al.
Pubblicazione: (2022)

Boosting Global-Local Feature Matching via Anomaly Synthesis for Multi-Class Point Cloud Anomaly Detection
di: Cheng, Yuqi, et al.
Pubblicazione: (2025)

Learning Unified Reference Representation for Unsupervised Multi-class Anomaly Detection
di: He, Liren, et al.
Pubblicazione: (2024)

CKNN: Cleansed k-Nearest Neighbor for Unsupervised Video Anomaly Detection
di: Yi, Jihun, et al.
Pubblicazione: (2024)

Dinomaly: The Less Is More Philosophy in Multi-Class Unsupervised Anomaly Detection
di: Guo, Jia, et al.
Pubblicazione: (2024)

Scale-Aware Contrastive Reverse Distillation for Unsupervised Medical Anomaly Detection
di: Li, Chunlei, et al.
Pubblicazione: (2025)

The MVTec AD 2 Dataset: Advanced Scenarios for Unsupervised Anomaly Detection
di: Heckler-Kram, Lars, et al.
Pubblicazione: (2025)