The invention discloses a target image quick retrieval method and system based on artificial intelligence. The method comprises the following steps of acquiring a template image and a plurality of known tags corresponding to the template image; extracting a to-be-detected image from the target image database; inputting the to-be-detected image and the template image into a trained convolutional neural network, and outputting a hash code of the to-be-detected image and a hash code of the template image; based on the Hamming distance between the Hash code of the to-be-detected image and the Hash code of the template image, obtaining the similarity between the to-be-detected image and the template image, and selecting one or more to-be-detected images with the similarity higher than a set threshold value as the retrieval results to be output. By using an artificial intelligence technology, based on the convolutional neural network, image features are extracted from image samples, collected by a robot vision platform, in a complex scene by using a Hash method, by introducing the distinguishing easy-to-confusion entities, a similarity relationship can be optimized, the sample attention is distinguished, and article retrieval in the complex scene can be better coped with.