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cs.CV2024
A Survey on RGB, 3D, and Multimodal Approaches for Unsupervised Industrial Image Anomaly Detection
Yuxuan Lin, Yang Chang, Xuan Tong +8
In the advancement of industrial informatization, unsupervised anomaly detection technology effectively overcomes the scarcity of abnormal samples and significantly enhances the au…
cs.CV2024
Suppressing Uncertainties in Degradation Estimation for Blind Super-Resolution
Junxiong Lin, Zeng Tao, Xuan Tong +10
The problem of blind image super-resolution aims to recover high-resolution (HR) images from low-resolution (LR) images with unknown degradation modes. Most existing methods model…
cs.CV2024
Adaptive Multi-modal Fusion of Spatially Variant Kernel Refinement with Diffusion Model for Blind Image Super-Resolution
Junxiong Lin, Yan Wang, Zeng Tao +10
Pre-trained diffusion models utilized for image generation encapsulate a substantial reservoir of a priori knowledge pertaining to intricate textures. Harnessing the potential of l…