Enhanced semantic segmentation of images

A non-transitory computer-readable storage medium having instructions stored thereon for semantic segmentation, which, when executed by a processor of a computing device cause the computing device to perform actions comprising:

• receiving image data comprising a set of pixels, wherein a first subset of the set of pixels is associated with an object;
• generating a coarse segmentation mask of a first resolution by identifying a second subset of the set of pixels approximating the first subset of the set of pixels;
• using a segmentation refinement model to generate an intermediate segmentation mask of a second resolution based on the image data and the coarse segmentation mask;
• using the segmentation refinement model to generate a refined segmentation mask of the first resolution based on the intermediate segmentation mask, the image data, and the coarse segmentation mask;
• and
• identifying a third subset of the set of pixels using the refined segmentation mask, wherein the third subset of the set of pixels is a closer approximation of the first subset of the set of pixels than the second subset of the set of pixels.

A method for segmenting an object that is visually depicted via a first subset of a set of pixels encoded by source image data, the method comprising:

• steps for receiving a coarse segmentation mask identifying a second subset of the set of pixels, wherein the second subset of the set of pixels is an approximation of the first subset of the set of pixels, and wherein the source image data and the coarse segmentation mask are of a first resolution;
• steps for using a segmentation refinement model to generate an intermediate segmentation mask of a second resolution based on the source image data and the coarse segmentation mask;
• steps for generating a refined segmentation mask of the first resolution based on the intermediate segmentation mask, the segmentation refinement model, the source image data, and the coarse segmentation mask;
• and
• steps for identifying a third subset of the set of pixels using the refined segmentation mask, wherein the third subset of the set of pixels is a closer approximation of the first subset of the set of pixels than the approximation of the second subset of the set of pixels.

A computing system for semantic segmentation, comprising:

• a processor device;
• and
• a computer-readable storage medium, coupled with the processor device, having instructions stored thereon, which, when executed by the processor device, perform actions comprising:
• generating a difference map based on a training coarse segmentation mask and a ground-truth (GT) segmentation mask corresponding to a training image, wherein the difference map indicates one or more differences between the training coarse segmentation mask and the GT segmentation mask;
• using the difference map, the training coarse segmentation mask, the training image, and the GT segmentation mask to train a segmentation refinement model;
• receiving image data comprising a set of pixels, wherein a first subset of the set of pixels associated with an object;
• generating a coarse segmentation mask that segments the image data by identifying a second subset of the set of pixels, wherein the second subset of the set of pixels is an approximation of the first subset of the set of pixels;
• and
• using the segmentation refinement model to generate a refined segmentation mask based on the image data and the coarse segmentation mask.