Abstract: The present disclosure belongs to the field of defect detections and discloses a method for constructing a defect detection model, a method for detecting a defect and a related apparatus, obtaining an initial training image, and adding a simulated anomaly to the initial training image to obtain a simulated anomaly training image; training a preset defect recognition model according to the initial training image and the simulated anomaly training image to obtain defect position information and mask prompt information; training a preset defect segmentation model according to the defect position information and the mask prompt information; and fusing the trained defect recognition model and defect segmentation model to obtain a defect detection model; the defect recognition model includes a teacher network branch, a student network branch and an autoencoder network branch; and an output difference between the teacher network branch and the student network branch is the defect position information.