Huawei Technologies Co., Limited

Bin Shao

Songcen Xu

Li Qian

Jun Yue

Hao Chen

Xueyan Huang

Youliang Yan

Chunhua Shen

Kunyang Sun

Yajiao Liu

A method and apparatus for updating an object recognition model in the field of artificial intelligence are disclosed. According to the method, a target image and first voice information of a user are obtained. The first voice information indicates a first category of a target object in the target image. A feature library of a first object recognition model is updated based on the target image and the first voice information. The updated first object recognition model includes a feature of the target object and a first label indicating the first category, and the feature of the target object corresponds to the first label. A recognition rate of an object recognition model can be improved more easily according to the technical solution provided in this application.

Method and apparatus for updating object recognition model

An instance segmentation method and apparatus are provided. A to-be-trained segmentation network performs the following processing on each instance group that is in a sample original image and that is of pixels of a marked instance, where each instance group includes at least one marked instance, and the processing includes: predicting at least two different first basic feature maps and a first attention feature map corresponding to each first basic feature map; performing weighted processing on the at least two first basic feature maps and pixel values of respective first attention feature maps corresponding to the at least two first basic feature maps, to obtain a first feature fusion map; and training the to-be-trained segmentation network based on the first feature fusion map and the sample original image. A segmentation model can precisely determine pixels of an instance in an original image.

Instance segmentation method and apparatus

A video generation method may be applied to the field of image processing and video generation in the field of artificial intelligence. The method includes: receiving a video generation instruction, and obtaining text information and image information in response to the video generation instruction, where the text information includes one or more keywords, and the image information includes N images; obtaining, based on the one or more keywords, one or more image features that is in each of the N images and corresponds to the one or more keywords; and inputting the one or more keywords and the one or more image features of the N images into a target generator network to generate a target video, where the target video includes M images, and the M images are generated based on the one or more image features of the N images and correspond to the one or more keywords.

Video generation method and related apparatus

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Shenzhen, China

Bin Shao