AHFNet dynamically weights four handpicked high-pass kernels (Sobel and temporal gradients) to extract sharpening features, reaching 33.25 dB PSNR on GOPRO with roughly one-sixth the training memory of heavier models.
Two deterministic half-quadratic regular- ization algorithms for computed imaging
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Adaptive High-Pass Kernel Prediction for Efficient Video Deblurring
AHFNet dynamically weights four handpicked high-pass kernels (Sobel and temporal gradients) to extract sharpening features, reaching 33.25 dB PSNR on GOPRO with roughly one-sixth the training memory of heavier models.