The invention relates to an image description method based on a conditional random field and internal semantic attention, and belongs to the technical field of crossing of computer vision and naturallanguage processing. The method comprises the steps: processing training data, designing a network structure model, extracting image features by adopting an existing convolutional neural network and atarget detection network, and designing a recurrent neural network with an internal semantic attention mechanism and an attention feature residual structure to generate a description corresponding toan image; adopting a mode of combining a cross entropy loss function and a conditional random field loss function as a training target, employing the processed training data for training a network model, and obtaining a network with an image semantic description generation function; and finally, inputting any image into the network to obtain a corresponding description. Compared with the prior art, the method has the advantages that the accuracy of sentence pattern generation of the description is guaranteed, the problem of repeated phrases in the generated description is solved, and the generated description can capture key information in the image better.
Image description method based on conditional random field and internal semantic attention