Target detection method and apparatus, model training method and apparatus, device, and storage medium

A model training apparatus, comprising:

• at least one memory configured to store program code;
• and
• at least one processor configured to read the program code and operate as instructed by the program code, the program code comprising:
• first obtaining code configured to cause at least one of the at least one processor to obtain a test style image corresponding to a training image through a first network model, and obtain a training style image corresponding to a test image through the first network model, the training image and the training style image belonging to a first domain, the test image and the test style image belonging to a second domain, and the first domain and the second domain being different domains
• second obtaining code configured to cause at least one of the at least one processor to, through a second network model, obtain a predicted probability value corresponding to a probability of a candidate region with respect to each class, the candidate region being a candidate bounding box extracted from the test image or the test style image;
• third obtaining code configured to cause at least one of the at least one processor to obtain a first prediction class probability value and a first prediction localization value, which are prediction values corresponding to the test style image and outputted by a region proposal network (RPN) of the second network model, and obtain a second prediction class probability value and a second prediction localization value, which are prediction values corresponding to the test style image outputted by a target detection network of the second network model;
• and
• training code configured to cause at least one of the at least one processor to train the first network model and the second network model by using a target loss function and according to the predicted probability value, the test style image, the training style image, the first prediction class probability value, the first prediction localization value, the second prediction class probability value, and the second prediction localization value, to obtain a cross-domain image detection model.

A terminal device comprising:

• at least one memory configured to store program code;
• and
• at least one processor configured to read the program code and operate as instructed by the program code, the program code comprising:
• first obtaining code configured to cause at least one of the at least one processor to obtain a first image belonging to a first domain, a second image corresponding to the first image, the second image belonging to a second domain, and the first domain and the second domain being different domains;
• second obtaining code configured to cause at least one of the at least one processor to obtain a detection result corresponding to the second image through a cross-domain image detection model, the detection result comprising target localization information and target class information of a target object, the target object being a detected object in the first image, the cross-domain image detection model comprising a first network model and a second network model, the first network model configured to convert an image from the first domain into an image in the second domain, and the second network model configured to perform region localization on the image in the second domain.