3 citations · 6 across the 13 of their papers we have counts for
13 papers
Real-IAD MVN: A Multi-View Normal Vector Dataset and Benchmark for High-Fidelity Industrial Anomaly Detection
Wenbing Zhu, Jianing Liang, Linjie Cheng +7
Industrial Anomaly Detection (IAD) is critical for quality control, but existing methods struggle with subtle, geometric defects. Standard 2D (RGB) images are sensitive to texture…
Real-IAD Variety: Pushing Industrial Anomaly Detection Dataset to a Modern Era
Wenbing Zhu, Chengjie Wang, Bin-Bin Gao +12
Industrial Anomaly Detection (IAD) is a cornerstone for ensuring operational safety, maintaining product quality, and optimizing manufacturing efficiency. However, the advancement…
Dinomaly2: A Unified Framework for Unsupervised Image Anomaly Detection
Jia Guo, Shuai Lu, Lei Fan +9
Unsupervised anomaly detection (UAD) has evolved from specialized single-class models to unified multi-class models, yet existing multi-class models significantly underperform the…
Pro-AD: Learning Comprehensive Prototypes with Prototype-based Constraint for Multi-class Unsupervised Anomaly Detection
Ziqing Zhou, Yurui Pan, Lidong Wang +4
Prototype-based reconstruction methods for unsupervised anomaly detection utilize a limited set of learnable prototypes which only aggregates insufficient normal information, resul…
Real-IAD D3: A Real-World 2D/Pseudo-3D/3D Dataset for Industrial Anomaly Detection
Wenbing Zhu, Lidong Wang, Ziqing Zhou +14
The increasing complexity of industrial anomaly detection (IAD) has positioned multimodal detection methods as a focal area of machine vision research. However, dedicated multimoda…
PA-CLIP: Enhancing Zero-Shot Anomaly Detection through Pseudo-Anomaly Awareness
Yurui Pan, Lidong Wang, Yuchao Chen +3
In industrial anomaly detection (IAD), accurately identifying defects amidst diverse anomalies and under varying imaging conditions remains a significant challenge. Traditional app…
OSV: One Step is Enough for High-Quality Image to Video Generation
Xiaofeng Mao, Zhengkai Jiang, Fu-Yun Wang +5
Video diffusion models have shown great potential in generating high-quality videos, making them an increasingly popular focus. However, their inherent iterative nature leads to su…
Dual-Interrelated Diffusion Model for Few-Shot Anomaly Image Generation
Ying Jin, Jinlong Peng, Qingdong He +8
The performance of anomaly inspection in industrial manufacturing is constrained by the scarcity of anomaly data. To overcome this challenge, researchers have started employing ano…
PSPU: Enhanced Positive and Unlabeled Learning by Leveraging Pseudo Supervision
Chengjie Wang, Chengming Xu, Zhenye Gan +3
Positive and Unlabeled (PU) learning, a binary classification model trained with only positive and unlabeled data, generally suffers from overfitted risk estimation due to inconsis…
SCL: Towards Domain Generalization via Single-Temporal Multimodal Contrastive Learning for Remote Sensing Change Detection
Qiangang Du, Jinlong Peng, Xu Chen +4
In recent years, change detection and anomaly detection models based on CNN and transformer have achieved remarkable success across various datasets based on paired data. However,…
Leveraging Fine-Grained Information and Noise Decoupling for Remote Sensing Change Detection
Qiangang Du, Jinlong Peng, Changan Wang +6
Change detection aims to identify remote sense object changes by analyzing data between bitemporal image pairs. Due to the large temporal and spatial span of data collection in cha…
Real-IAD: A Real-World Multi-View Dataset for Benchmarking Versatile Industrial Anomaly Detection
Chengjie Wang, Wenbing Zhu, Bin-Bin Gao +6
Industrial anomaly detection (IAD) has garnered significant attention and experienced rapid development. However, the recent development of IAD approach has encountered certain dif…
Learning Unified Reference Representation for Unsupervised Multi-class Anomaly Detection
Liren He, Zhengkai Jiang, Jinlong Peng +7
In the field of multi-class anomaly detection, reconstruction-based methods derived from single-class anomaly detection face the well-known challenge of "learning shortcuts", where…