KernFusNet: Implicit Kernel Modulation and Fusion for Blind Super-Resolution
Mehta, Nancy ; Dudhane, Akshay A. ; Murala, Subrahmanyam ; Timofte, Radu
Mehta, Nancy
Dudhane, Akshay A.
Murala, Subrahmanyam
Timofte, Radu
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Department
Computer Vision
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Type
Conference proceeding
Date
2025
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Language
English
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Abstract
Convolutional neural network-based super-resolution (SR) methods have achieved significant success on ideal, predefined downsampling (bicubic) kernels. However, these algorithms struggle with unknown degradations in real-world data, which often follow a spatially variant and unknown distribution. Recently proposed blind SR studies address this issue by estimating degradation kernels, but their results often exhibit artifacts and detail deformation due to redundant information being considered in kernel estimation. Additionally, effective merging of the estimated kernels into the feature space of the SR network is challenging. To overcome these issues, we introduce a novel network, KernFusNet which simultaneously learns the kernel degradation and the relevant content information to adapt to the blur characteristics in real-world images. Specifically, KernFusNet comprises two components: an Implicit Kernel Estimation (IKE) module and a Kernel-Prior Oriented Detail Fusion (KPDF) module. The IKE module estimates the degradation kernel from low-resolution contexts, while the KPDF module effectively merge the relevant information on the basis of the learned degradations in both high-resolution and low-resolution spaces. Comprehensive experiments on the real-world and synthetic datasets show that our network achieves state-of-the-art performance for blind SR.
Citation
N. Mehta, A. Dudhane, S. Murala and R. Timofte, "KernFusNet: Implicit Kernel Modulation and Fusion for Blind Super-Resolution," 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Nashville, TN, USA, 2025, pp. 823-833, doi: 10.1109/CVPRW67362.2025.00087.
Source
IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Conference
2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2025
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Source
2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2025
Publisher
IEEE
