An automatic labeling apparatus for object recognition and a method therefor are provided. The automatic labeling apparatus for object recognition is configured to apply an object recognition algorithm to each of a plurality of image frames so as to recognize an object, and in response to a determination that an object recognition result in at least one first image frame among the image frames corresponds to a predetermined error condition, automatically generate a data set on an object which is a target of object recognition by using an object recognition result of a second image frame other than the first image frame among the image frames and an object image of the first image frame. The object recognition algorithm, which is a neural network model generated through machine learning, may be stored in a memory or provided through a server in an artificial intelligence environment through a 5G network.