End-to-end panoramic image segmentation method based on query vector

Abstract

The invention discloses an end-to-end panoramic image segmentation method based on a query vector. The method comprises the following steps: representing a panoramic image segmentation process and an output result by using the query vector; enabling the query vector (Object Query) to comprise a foreground query vector (Thing Query) and a background query vector (Stuff Query); establishing a panoramic image segmentation model, including respectively establishing an image foreground class segmentation model and an image background class segmentation model; respectively mapping the foreground query vector and the background query vector to an image foreground class segmentation result things and an image background class segmentation result stuff; and carrying out detection training based on the foreground query vector and the background query vector, so that the detection training time of the foreground target is shortened, and end-to-end training and foreground segmentation result and background segmentation result output are realized. The method is simpler in process, lower in calculation complexity and better in performance.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to a panoramic image segmentation method, in particular to an end-to-end panoramic image segmentation method based on a query vector. Background technique [0002] Panoptic Segmentation is a challenging task whose goal is to assign a semantic label and unique identity to each image pixel. The image segmentation model method needs to adopt a unified way to represent the image foreground class (things) and the image background class (stuff). A major problem comes from the conflict in the number of image foreground classes and image background classes, because the number of image foreground classes is dynamic and changeable, while the number of image background classes is fixed. Panoramic image segmentation technology is an important technology for comprehensive research and understanding of scenes, and it can solve technical problems in some specific fields, including the perc...

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the deficiencies in the prior art above, the present invention provides an end-to-end panoramic image segmentation method based on query vectors, which is a new model method for panoramic image segmentation based on query vectors, and establishes image foreground classes and background classes respectively. Splitting the model can simultaneously solve the two key technical problems of long model training time and complicated calculation method flow

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