System and method for training a model to perform semantic segmentation on low visibility images using high visibility images having a close camera view

A system for training a model to be used for semantic segmentation of images taken under low visibility conditions, comprising:

• a module for obtaining a plurality of sets of images, each set of images being associated with an index z comprised between 1 and Z, the index z indicating a level of visibility of the images of the set of images changing from 1 to Z, wherein the model is initially trained to perform semantic segmentation under the level of visibility of level 1,
• a module for iteratively training the model configured to perform:
• a—for each z above 1, obtaining preliminary semantic segmentation labels for each image of the set of images of index z−1 by applying the model to each image of the set of images of index z−1,
• b—processing each preliminary semantic segmentation labels using semantic segmentation labels obtained using the model on a selected image of the set of images of index 1, the selected image being selected as the image having a camera view which is closest to a camera view of the image associated with the preliminary semantic segmentation label, and obtaining processed semantic segmentation labels,
• c—training the model using the set of images of index z−1 and the associated processed semantic segmentation labels, and
• d—performing steps a to c for z+1.