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English(EN) AFP-GIC: Controllable Generative Image Compression [R]

AFP-GIC 推动可控生成图像压缩，降低延迟

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了用于可控生成图像压缩的自适应融合先验迁移（AFP-GIC）框架，该框架旨在提高极低比特率下的重建质量。AFP-GIC 利用预训练模型的自适应融合先验来指导潜在表示的形成和重建，使其能够在不传输先验本身的情况下合成缺失的细节。与 DC-VIC 等现有最先进的方法相比，这种方法降低了解码器延迟和推理参数数量，同时实现了具有竞争力的性能指标和明显的感知优势。 AI

影响 这项研究可能带来更高效的图像和视频压缩，影响流媒体服务和数据存储。

排序理由 该集群描述了一篇关于新型图像压缩框架的最新研究论文。

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AFP-GIC 推动可控生成图像压缩，降低延迟

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该集群描述了一篇关于新型图像压缩框架的最新研究论文。
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报道来源 [2]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    可控生成图像压缩的自适应融合先验迁移

    Learned image compression achieves competitive rate-distortion performance, but very-low-bitrate reconstruction remains challenging because the transmitted representation cannot preserve fine textures and local structures. Perceptual and generative codecs synthesize missing detai…

  2. r/MachineLearning TIER_1 English(EN) · /u/WuPeter6687298 ·

    AFP-GIC：可控生成图像压缩 [R]

    <table> <tr><td> <a href="https://www.reddit.com/r/MachineLearning/comments/1wzbe6r/afpgic_controllable_generative_image_compression_r/"> <img alt="AFP-GIC: Controllable Generative Image Compression [R]" src="https://preview.redd.it/qg5irsv3cwth1.png?width=640&amp;crop=smart&amp;…

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