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English(EN) Semantic-Guided Frequency Modulation for Learned Image Compression

新的SG-AFM方法将学习式图像压缩提升13%

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了一种名为语义引导自适应潜在频率调制（SG-AFM）的新方法，以改进学习式图像压缩。该技术利用语义信息来引导图像数据中高频的衰减，从而在不牺牲物体边界等关键细节的情况下降低数据速率。SG-AFM应用Haar小波变换以及固定和学习到的乘数组合来调制频率子带，在各种数据集上实现了显著的比特率降低。 AI

排序理由 该集群包含一篇详细介绍图像压缩新方法的学术论文。[lever_c_demoted from research: ic=1 ai=0.4]

在 arXiv cs.CV 阅读 →

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新的SG-AFM方法将学习式图像压缩提升13%

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该集群包含一篇详细介绍图像压缩新方法的学术论文。[lever_c_demoted from research: ic=1 ai=0.4]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Gangyi Tian, Wen Ji, Alireza Furutanpey, Mingxuan Li ·

    用于学习式图像压缩的语义引导频率调制

    arXiv:2610.33616v1 Announce Type: cross Abstract: High-frequency attenuation can reduce the rate of learned image codecs but also remove object boundaries and fine detail. We propose Semantic-Guided Adaptive Latent-Frequency Modulation (SG-AFM), which uses a semantic structural p…

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