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SYSTEMS AND METHODS FOR PROCESSING AUDIOVISUAL DATA USING LATENT CODES FROM GENERATIVE NETWORKS AND MODELS

机译:使用生成网络和模型的潜在代码处理视听数据的系统和方法

摘要

Systems and methods for viewing, storing, transmitting, searching, and editing application-specific audiovisual content (or other unstructured data) are disclosed in which edge devices generate content on the fly from a partial set of instructions rather than merely accessing the content in its final or near-final form. An image processing architecture may include a generative model that may be a deep learning model. The generative model may include a latent space comprising a plurality of latent codes and a trained generator mapping. The trained generator mapping may convert points in the latent space to uncompressed data points, which in the case of audiovisual content may be generated image frames. The generative model may be capable of closely approximating (up to noise or perceptual error) most or all potential data points in the relevant compression application, which in the case of audiovisual content may be source images.
机译:公开了用于查看,存储,发送,搜索和编辑应用专用的视听内容(或其他非结构化数据)的系统和方法,其中边缘设备从一组指令飞行地生成内容,而不是仅仅访问其内容最终或近最终表格。图像处理架构可以包括可能是深度学习模型的生成模型。生成模型可以包括包括多个潜在码和训练发生器映射的潜在空间。训练有素的生成器映射可以将潜在空间中的点转换为未压缩的数据点,在视听内容的情况下可以生成图像帧。生成模型可以能够在相关压缩应用中的大多数或所有潜在的数据点密切地近似(达到噪声或感知误差),这在视听内容的情况下可以是源图像。

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