1 citations · 1 across the 4 of their papers we have counts for
6 papers
Establishing Stochastic Object Models from Noisy Data via Ambient Measurement-Integrated Diffusion
Xiaoning Lei, Jianwei Sun, Wenhao Cai +3
Task-based measures of image quality (IQ) are critical for evaluating medical imaging systems, which must account for randomness including anatomical variability. Stochastic object…
ASBench: Image Anomalies Synthesis Benchmark for Anomaly Detection
Qunyi Zhang, Songan Zhang, Jiaqi Liu +5
Anomaly detection plays a pivotal role in manufacturing quality control, yet its application is constrained by limited abnormal samples and high manual annotation costs. While anom…
STAGE: Segmentation-oriented Industrial Anomaly Synthesis via Graded Diffusion with Explicit Mask Alignment
Xichen Xu, Yanshu Wang, Jinbao Wang +5
Segmentation-oriented Industrial Anomaly Synthesis (SIAS) plays a pivotal role in enhancing the performance of downstream anomaly segmentation, as it provides an effective means of…
FAST: Foreground-aware Diffusion with Accelerated Sampling Trajectory for Segmentation-oriented Anomaly Synthesis
Xichen Xu, Yanshu Wang, Jinbao Wang +4
Industrial anomaly segmentation relies heavily on pixel-level annotations, yet real-world anomalies are often scarce, diverse, and costly to label. Segmentation-oriented industrial…
SARD: Segmentation-Aware Anomaly Synthesis via Region-Constrained Diffusion with Discriminative Mask Guidance
Yanshu Wang, Xichen Xu, Xiaoning Lei +1
Synthesizing realistic and spatially precise anomalies is essential for enhancing the robustness of industrial anomaly detection systems. While recent diffusion-based methods have…
A Survey on Industrial Anomaly Synthesis
Yanshu Wang, Xichen Xu, Jiaqi Liu +6
This paper presents a comprehensive review of industrial anomaly synthesis (IAS). Existing surveys on industrial anomalies mainly focus on anomaly detection, while IAS is typically…