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New SG-AFM method enhances learned image compression by 13%

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new method called Semantic-Guided Adaptive Latent-Frequency Modulation (SG-AFM) to improve learned image compression. This technique uses semantic information to guide the attenuation of high frequencies in image data, reducing the data rate without sacrificing crucial details like object boundaries. SG-AFM applies a Haar wavelet transform and a combination of fixed and learned multipliers to modulate frequency subbands, achieving significant bitrate reductions across various datasets. AI

RANK_REASON The cluster contains a research paper detailing a new method for image compression. [lever_c_demoted from research: ic=1 ai=0.4]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New SG-AFM method enhances learned image compression by 13%

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The cluster contains a research paper detailing a new method for image compression. [lever_c_demoted from research: ic=1 ai=0.4]
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COVERAGE [1]

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

    Semantic-Guided Frequency Modulation for Learned Image Compression

    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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