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Found 11 papers, 9 papers with code
Customizing Visual-Language Foundation Models for Multi-modal Anomaly Detection and Reasoning
In addition, we unify the input representation of multi-modality into a 2D image format, enabling multi-modal anomaly detection and reasoning.
Dual-path Frequency Discriminators for Few-shot Anomaly Detection
We consider anomaly detection as a discriminative classification problem, wherefore the dual-path feature discrimination module is employed to detect and locate the image-level and feature-level anomalies in the feature space.
A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect
Visual Anomaly Detection (VAD) endeavors to pinpoint deviations from the concept of normality in visual data, widely applied across diverse domains, e. g., industrial defect inspection, and medical lesion detection.
Generative Denoise Distillation: Simple Stochastic Noises Induce Efficient Knowledge Transfer for Dense Prediction
Knowledge distillation is the process of transferring knowledge from a more powerful large model (teacher) to a simpler counterpart (student).
Towards Generic Anomaly Detection and Understanding: Large-scale Visual-linguistic Model (GPT-4V) Takes the Lead
This study explores the use of GPT-4V(ision), a powerful visual-linguistic model, to address anomaly detection tasks in a generic manner.
2nd Place Winning Solution for the CVPR2023 Visual Anomaly and Novelty Detection Challenge: Multimodal Prompting for Data-centric Anomaly Detection
This technical report introduces the winning solution of the team Segment Any Anomaly for the CVPR2023 Visual Anomaly and Novelty Detection (VAND) challenge.
Segment Any Anomaly without Training via Hybrid Prompt Regularization
We present a novel framework, i. e., Segment Any Anomaly + (SAA+), for zero-shot anomaly segmentation with hybrid prompt regularization to improve the adaptability of modern foundation models.
Ranked #1 on
Anomaly Detection
on KSDD2
Complementary Pseudo Multimodal Feature for Point Cloud Anomaly Detection
The 3D and 2D modality features are aggregated to obtain the CPMF for PCD anomaly detection.
Ranked #1 on
Depth Anomaly Detection and Segmentation
on MVTEC 3D-AD
(using extra training data)
3D Anomaly Detection and Segmentation
Depth Anomaly Detection and Segmentation
Collaborative Discrepancy Optimization for Reliable Image Anomaly Localization
CDO introduces a margin optimization module and an overlap optimization module to optimize the two key factors determining the localization performance, i. e., the margin and the overlap between the discrepancy distributions (DDs) of normal and abnormal samples.
Ranked #1 on
Anomaly Detection
on MVTEC 3D-AD
(using extra training data)
Informative knowledge distillation for image anomaly segmentation
However, rare attention has been paid to the overfitting problem caused by the inconsistency between the capacity of the neural network and the amount of knowledge in this scheme.
Ranked #27 on
Anomaly Detection
on MVTec AD
(Segmentation AUPRO metric)
Position Encoding Enhanced Feature Mapping for Image Anomaly Detection
Image anomaly detection is an important stage for automatic visual inspection in intelligent manufacturing systems.
Ranked #11 on
Anomaly Detection
on MVTec AD
(Segmentation AUPRO metric)
