133 citations · 137 across the 3 of their papers we have counts for
11 papers · 1 filter
INP-Former++: Advancing Universal Anomaly Detection via Intrinsic Normal Prototypes and Residual Learning
Wei Luo, Haiming Yao, Yunkang Cao +4
Anomaly detection (AD) is essential for industrial inspection and medical diagnosis, yet existing methods typically rely on ``comparing'' test images to normal references from a tr…
VarAD: Lightweight High-Resolution Image Anomaly Detection via Visual Autoregressive Modeling
Yunkang Cao, Haiming Yao, Wei Luo +1
This paper addresses a practical task: High-Resolution Image Anomaly Detection (HRIAD). In comparison to conventional image anomaly detection for low-resolution images, HRIAD impos…
LiftImage3D: Lifting Any Single Image to 3D Gaussians with Video Generation Priors
Yabo Chen, Chen Yang, Jiemin Fang +6
Single-image 3D reconstruction remains a fundamental challenge in computer vision due to inherent geometric ambiguities and limited viewpoint information. Recent advances in Latent…
RAD: A Comprehensive Dataset for Benchmarking the Robustness of Image Anomaly Detection
Yuqi Cheng, Yunkang Cao, Rui Chen +1
Robustness against noisy imaging is crucial for practical image anomaly detection systems. This study introduces a Robust Anomaly Detection (RAD) dataset with free views, uneven il…
Prior Normality Prompt Transformer for Multi-class Industrial Image Anomaly Detection
Haiming Yao, Yunkang Cao, Wei Luo +3
Image anomaly detection plays a pivotal role in industrial inspection. Traditional approaches often demand distinct models for specific categories, resulting in substantial deploym…
Global-Regularized Neighborhood Regression for Efficient Zero-Shot Texture Anomaly Detection
Haiming Yao, Wei Luo, Yunkang Cao +3
Texture surface anomaly detection finds widespread applications in industrial settings. However, existing methods often necessitate gathering numerous samples for model training. M…