An object attitude estimation method and system based on an image and a three-dimensional model, and a medium. The method comprises the following steps: acquiring image data of a target object; and performing feature extraction on the image data, mapping extracted features by using an object attitude estimation model, acquiring a viewing angle corresponding to the feature having the highest similarity, and taking the viewing angle as an estimated target object pose, wherein the object attitude estimation model is used for mapping image features of the target object to a convolutional neural network of a three-dimensional model multi-viewing-angle feature having the highest similarity. By means of the method, the aid of a depth image is not required, a three-dimensional model of a target object is more fully utilized, a blocked target object can be better calculated, and when modifying the target object, the retraining of the entire network is not required, such that the generalizability, precision and recognition speed of object pose estimation technology are improved, and the method can be widely applied to the technical field of intelligent information processing.
OBJECT ATTITUDE ESTIMATION METHOD AND SYSTEM BASED ON IMAGE AND THREE-DIMENSIONAL MODEL, AND MEDIUM