:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Jin, Wenping, Tang, Yuyang, Zhu, Li
Format:	Preprint
Published:	2026
Subjects:	Computer Vision and Pattern Recognition
Online Access:	https://arxiv.org/abs/2602.07694
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Two-Stage Detection-Tracking Framework for Stable Apple Quality Inspection in Dense Conveyor-Belt Environments
by: Park, Keonvin, et al.
Published: (2026)

Decoupled Complementary Spectral-Spatial Learning for Background Representation Enhancement in Hyperspectral Anomaly Detection
by: Jin, Wenping, et al.
Published: (2025)

Normality Prior Guided Multi-Semantic Fusion Network for Unsupervised Image Anomaly Detection
by: Xu, Muhao, et al.
Published: (2025)

Correcting Deviations from Normality: A Reformulated Diffusion Model for Multi-Class Unsupervised Anomaly Detection
by: Beizaee, Farzad, et al.
Published: (2025)

BeltCrack: the First Sequential-image Industrial Conveyor Belt Crack Detection Dataset and Its Baseline with Triple-domain Feature Learning
by: Huang, Jianghong, et al.
Published: (2025)

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

Morphology-optimized Multi-Scale Fusion: Combining Local Artifacts and Mesoscopic Semantics for Deepfake Detection and Localization
by: Shuai, Chao, et al.
Published: (2025)

Aligning First, Then Fusing: A Novel Weakly Supervised Multimodal Violence Detection Method
by: Jin, Wenping, et al.
Published: (2025)

AnomalyFactory: Regard Anomaly Generation as Unsupervised Anomaly Localization
by: Zhao, Ying
Published: (2024)

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

Memory-Augmented Dual-Decoder Networks for Multi-Class Unsupervised Anomaly Detection
by: Xing, Jingyu, et al.
Published: (2025)

Feed-Forward SceneDINO for Unsupervised Semantic Scene Completion
by: Jevtić, Aleksandar, et al.
Published: (2025)

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

Exploring Plain ViT Reconstruction for Multi-class Unsupervised Anomaly Detection
by: Zhang, Jiangning, et al.
Published: (2023)

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

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

Unified Multimodal Coherent Field: Synchronous Semantic-Spatial-Vision Fusion for Brain Tumor Segmentation
by: Zhang, Mingda, et al.
Published: (2025)

BoMuDANet: Unsupervised Adaptation for Visual Scene Understanding in Unstructured Driving Environments
by: Kothandaraman, Divya, et al.
Published: (2020)

RcAE: Recursive Reconstruction Framework for Unsupervised Industrial Anomaly Detection
by: Wu, Rongcheng, et al.
Published: (2025)

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

Semantic Iterative Reconstruction: One-Shot Universal Anomaly Detection
by: Zhu, Ning
Published: (2026)

MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection
by: He, Haoyang, et al.
Published: (2024)

Pro-AD: Learning Comprehensive Prototypes with Prototype-based Constraint for Multi-class Unsupervised Anomaly Detection
by: Zhou, Ziqing, et al.
Published: (2025)

Quality-Aware Language-Conditioned Local Auto-Regressive Anomaly Synthesis and Detection
by: Qian, Long, et al.
Published: (2025)

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

Multi-View Industrial Anomaly Detection with Epipolar Constrained Cross-View Fusion
by: Liu, Yifan, et al.
Published: (2025)

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

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

Unsupervised Learning Based Multi-Scale Exposure Fusion
by: Zheng, Chaobing, et al.
Published: (2024)

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

Dynamic Attention and Bi-directional Fusion for Safety Helmet Wearing Detection
by: Feng, Junwei, et al.
Published: (2024)

Attention Fusion Reverse Distillation for Multi-Lighting Image Anomaly Detection
by: Zhang, Yiheng, et al.
Published: (2024)

Boosting 3D Object Detection with Semantic-Aware Multi-Branch Framework
by: Jing, Hao, et al.
Published: (2024)

Zero-Shot Anomaly Detection with Dual-Branch Prompt Selection
by: Wang, Zihan, et al.
Published: (2025)

One-Step Detection Paradigm for Hyperspectral Anomaly Detection via Spectral Deviation Relationship Learning
by: Li, Jingtao, et al.
Published: (2023)

FiLo++: Zero-/Few-Shot Anomaly Detection by Fused Fine-Grained Descriptions and Deformable Localization
by: Gu, Zhaopeng, et al.
Published: (2025)

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

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

Analysis of Unstructured High-Density Crowded Scenes for Crowd Monitoring
by: Matov, Alexandre
Published: (2024)

Structural Teacher-Student Normality Learning for Multi-Class Anomaly Detection and Localization
by: Deng, Hanqiu, et al.
Published: (2024)