To solve the problem of the lack of use of shallow image features in image captions and insufficient extraction of image objects,an image caption generation algorithm based on attention image feature extraction is proposed.Through context information of a language model,adaptive attention weight assignment is performed on different depth image features to ensure that the attention-grabbing image features guide the image caption generation,thereby improving the image caption effect.In the MSCOCO test set,the BLEU-1 and CIDEr scores of the proposed algorithm reached 0.752 and 0.934,respectively,thus verifying the effectiveness of the proposed method.