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Multi-model techniques to generate video metadata

机译:生成视频元数据的多模型技术

摘要

A metadata generation system utilizes machine learning techniques to accurately describe content of videos based on multi-model predictions. In some embodiments, multiple feature sets are extracted from a video, including feature sets showing correlations between additional features of the video. The feature sets are provided to a learnable pooling layer with multiple modeling techniques, which generates, for each of the feature sets, a multi-model content prediction. In some cases, the multi-model predictions are consolidated into a combined prediction. Keywords describing the content of the video are determined based on the multi-model predictions (or combined prediction). An augmented video is generated with metadata that is based on the keywords.
机译:元数据生成系统利用机器学习技术基于多模型预测来准确描述视频内容。在一些实施例中,从视频提取多个特征集,包括示出视频的附加特征之间的相关性的特征集。将特征集提供给具有多种建模技术的可学习池化层,该建模技术可为每个特征集生成多模型内容预测。在某些情况下,将多模型预测合并为组合预测。基于多模型预测(或组合预测)来确定描述视频内容的关键字。使用基于关键字的元数据生成增强视频。

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