The article introduces HFUR, a neural network architecture for enhancing compressed video quality by focusing on frequency-based upsampling and iterative refinement. Video compression artifacts are addressed through the proposed modules: ImpFreqUp and HIR. ImpFreqUp utilizes DCT-domain prior to reconstruct loss, while HIR refines feature maps hierarchically. Extensive experiments demonstrate the effectiveness of HFUR in achieving state-of-the-art performance.
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by Qianyu Zhang... alle arxiv.org 03-19-2024
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