1 citations · 1 across the 11 of their papers we have counts for
12 papers
From Physical Degradation Models to Task-Aware All-in-One Image Restoration
Hu Gao, Xiaoning Lei, Xichen Xu +2
All-in-one image restoration aims to adaptively handle multiple restoration tasks with a single trained model. Although existing methods achieve promising results by introducing pr…
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…
Physically Interpretable Multi-Degradation Image Restoration via Deep Unfolding and Explainable Convolution
Hu Gao, Xiaoning Lei, Xichen Xu +2
Although image restoration has advanced significantly, most existing methods target only a single type of degradation. In real-world scenarios, images often contain multiple degrad…
Learning to Restore Multi-Degraded Images via Ingredient Decoupling and Task-Aware Path Adaptation
Hu Gao, Xiaoning Lei, Ying Zhang +3
Image restoration (IR) aims to recover clean images from degraded observations. Despite remarkable progress, most existing methods focus on a single degradation type, whereas real-…
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…
MBMamba: When Memory Buffer Meets Mamba for Structure-Aware Image Deblurring
Hu Gao, Xiaoning Lei, Xichen Xu +2
The Mamba architecture has emerged as a promising alternative to CNNs and Transformers for image deblurring. However, its flatten-and-scan strategy often results in local pixel for…
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…
Unsupervised Generation of Pseudo Normal PET from MRI with Diffusion Model for Epileptic Focus Localization
Wentao Chen, Jiwei Li, Xichen Xu +6
[F]fluorodeoxyglucose (FDG) positron emission tomography (PET) has emerged as a crucial tool in identifying the epileptic focus, especially in cases where magnetic resonance…
Ambient-Pix2PixGAN for Translating Medical Images from Noisy Data
Wentao Chen, Xichen Xu, Jie Luo +1
Image-to-image translation is a common task in computer vision and has been rapidly increasing the impact on the field of medical imaging. Deep learning-based methods that employ c…
AmbientCycleGAN for Establishing Interpretable Stochastic Object Models Based on Mathematical Phantoms and Medical Imaging Measurements
Xichen Xu, Wentao Chen, Weimin Zhou
Medical imaging systems that are designed for producing diagnostically informative images should be objectively assessed via task-based measures of image quality (IQ). Ideally, com…