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Anomaly Localization

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Showing 51–75 of 101 papers

TitleStatusHype
Industrial Anomaly Detection and Localization Using Weakly-Supervised Residual Transformers—0
Segment Any Anomaly without Training via Hybrid Prompt RegularizationCode2
Unsupervised anomaly localization in high-resolution breast scans using deep pluralistic image completionCode0
High-Fidelity Zero-Shot Texture Anomaly Localization Using Feature Correspondence AnalysisCode1
Unsupervised Anomaly Detection and Localization of Machine Audio: A GAN-based ApproachCode1
ISSTAD: Incremental Self-Supervised Learning Based on Transformer for Anomaly Detection and LocalizationCode0
Hard-normal Example-aware Template Mutual Matching for Industrial Anomaly DetectionCode1
Collaborative Discrepancy Optimization for Reliable Image Anomaly LocalizationCode1
Adapting the Hypersphere Loss Function from Anomaly Detection to Anomaly Segmentation—0
Removing Anomalies as Noises for Industrial Defect Localization—0
OmniAL: A Unified CNN Framework for Unsupervised Anomaly Localization—0
EVAL: Explainable Video Anomaly Localization—0
Multi-scale Feature Imitation for Unsupervised Anomaly Localization—0
Masked Transformer for image Anomaly Localization—0
ADPS: Asymmetric Distillation Post-Segmentation for Image Anomaly Detection—0
Anomaly localization for copy detection patterns through print estimations—0
Visual Anomaly Detection Via Partition Memory Bank Module and Error Estimation—0
Unsupervised Anomaly Localization with Structural Feature-AutoencodersCode1
Consistency-based Self-supervised Learning for Temporal Anomaly LocalizationCode1
DSR -- A dual subspace re-projection network for surface anomaly detectionCode1
Deep Learning for Unsupervised Anomaly Localization in Industrial Images: A Survey—0
Enhancing Generative Networks for Chest Anomaly Localization through Automatic Registration-Based Unpaired-to-Pseudo-Paired Training Data Translation—0
Unsupervised Industrial Anomaly Detection via Pattern Generative and Contrastive Networks—0
CFA: Coupled-hypersphere-based Feature Adaptation for Target-Oriented Anomaly LocalizationCode1
A Unified Model for Multi-class Anomaly DetectionCode2
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