Tencent Technology (shenzhen) Company Limited

Jiebo Luo

Yan Zhang

Lin Ma

Yang Feng

Embodiments of this application disclose a method for training an image caption model, the image caption model including an encoding convolutional neural network (CNN) and a decoding recurrent neural network (RNN). The method includes: obtaining an image eigenvector of an image sample by using the encoding CNN; decoding the image eigenvector by using the decoding RNN, to obtain a sentence used for describing the image sample; determining a matching degree between the sentence obtained through decoding and the image sample and a smoothness degree of the sentence obtained through decoding, respectively; and adjusting the decoding RNN according to the matching degree and the smoothness degree.

Method and apparatus for training image caption model, and storage medium

A video query method includes obtaining a media feature of a query media and a static image feature corresponding to a candidate video. The query media includes the target object, and the candidate video includes the moving object. A video feature of the candidate video is determined according to the static image feature and motion time sequence information of the moving object in the candidate video. Whether the moving object in the candidate video is related to the target object in the query media can be determined according to the media feature and the video feature.

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Shenzhen, China

Jiebo Luo