Generative Compression

Shibani Santurkar, D. Budden, N. Shavit
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引用次数: 174

Abstract

Traditional image and video compression algorithms rely on hand-crafted encoder/decoder pairs (codecs) that lack adaptability and are agnostic to the data being compressed. We describe the concept of generative compression, the compression of data using generative models, and suggest that it is a direction worth pursuing to produce more accurate and visually pleasing reconstructions at deeper compression levels for both image and video data. We also show that generative compression is orders- of-magnitude more robust to bit errors (e.g., from noisy channels) than traditional variable-length coding schemes.
生成压缩
传统的图像和视频压缩算法依赖于手工制作的编码器/解码器对(编解码器),缺乏适应性,并且对被压缩的数据不可知。我们描述了生成压缩的概念,使用生成模型对数据进行压缩,并建议在更深的压缩水平上为图像和视频数据产生更准确和视觉上令人愉悦的重建是一个值得追求的方向。我们还表明,生成压缩比传统的变长编码方案对比特错误(例如,来自噪声信道)更具数量级的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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