Abstract: A method and system for dimension estimation based on duplication identification is disclosed. In some embodiments, the method includes receiving a set of images of an object. The method includes detecting, from each image in the set of images, a respective image segmentation representing a damage of the object. The method then includes determining a respective dimension for the damage represented by each of the image segmentations. The method further includes determining whether two or more of the image segmentations represent a same damage of the object. Responsive to two or more of the image segmentations representing a same damage of the object, the method includes combining the respective dimensions determined for the damage represented by the two or more image segmentations to obtain a final dimension for the same damage.

Abstract: A method for dimension estimation based on duplication identification. In some embodiments, the method includes receiving a set of images of an object. The method then includes detecting, using a first machine learning system trained to perform image segmentation, a first image segmentation representing a damage of the object on a first image and a second image segmentation representing a damage of the object on a second image. The method further includes determining, using a second machine learning system trained to perform dimension estimation, a first dimension for the damage represented by the first image segmentation and a second dimension for the damage represented by the second image segmentation. The method includes determining whether the first and second image segmentations represent a same damage. If these image segmentations represent the same damage, the method intelligently combines the first and second dimensions to obtain a final dimension for the damage.

Abstract: A method for dimension estimation based on duplication identification. In some embodiments, the method includes receiving a set of images of an object. The method then includes detecting, using a first machine learning system trained to perform image segmentation, a first image segmentation representing a damage of the object on a first image and a second image segmentation representing a damage of the object on a second image. The method further includes determining, using a second machine learning system trained to perform dimension estimation, a first dimension for the damage represented by the first image segmentation and a second dimension for the damage represented by the second image segmentation. The method includes determining whether the first and second image segmentations represent a same damage. If these image segmentations represent the same damage, the method intelligently combines the first and second dimensions to obtain a final dimension for the damage.