An assembly change detection method based on an attention mechanism includes establishing a three-dimensional model of an assembly body, adding a tag to each part in the three-dimensional model, setting several assembly nodes, obtaining depth images of the three-dimensional model under each assembly node in different viewing angles, and obtaining a change tag image of a newly added part at each assembly node; selecting two depth images at front and back moments in different viewing angles as training samples; performing semantic fusion, feature extraction, attention mechanism processing and metric learning sequentially on the training samples, training a detection model, continuously selecting training samples to train the detection model, saving model parameters with the optimal similarity during the training process, and completing the training; and obtaining depth images of two successive assembly nodes in the assembly process of the assembly body to be detected, inputting the depth images into the trained detection model, and outputting the change image of the newly added part of the assembly body in the assembly process.
ASSEMBLY BODY CHANGE DETECTION METHOD, DEVICE AND MEDIUM BASED ON ATTENTION MECHANISM