Beijing Sensetime Technology Development Co., Ltd.

Yixiao Ge

Dapeng Chen

Hongsheng Li

Xiaogang Wang

Yantao Shen

The present disclosure discloses an image processing method and related device thereof. The method includes: acquiring an image to be processed; and performing a feature extraction process on the image to be processed using a target neural network so as to obtain target feature data of the image to be processed, wherein parameters of the target neural network are time average values of parameters of a first neural network which is obtained from training under supervision by a training image set and an average network, and parameters of the average network are time average values of parameters of a second neural network which is obtained from training under supervision by the training image set and the target neural network. A corresponding device is also disclosed. Feature data of image to be processed are obtained via the feature extraction process performed on the image to be processed.

Image processing method, image processing device, and storage medium

The present disclosure relates to a network optimization method and apparatus, an image processing method and apparatus, and a storage medium. The network optimization method includes: obtaining an image sample group; obtaining a first feature and a second feature of an image in the image sample group, and obtaining a first classification result by using the first feature of the image; performing feature exchange processing on an image pair in the image sample group to obtain a new image pair; obtaining a first loss value of the first classification result, a second loss value of the new image pair, and a third loss value of first features and second features of the new image pair in a preset manner; and adjusting parameters of a neural network at least according to the first loss value, the second loss value, and the third loss value until a preset requirement is met.

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Beijing, China

Yixiao Ge