Computer vision system and method

A method of training a model, said model for segmenting an image, the model comprising:

• a first neural network having a plurality of layers comprising at least one separable convolution module configured to perform separable convolutions;
• a second neural network with a plurality of layers, comprising at least one separable convolution module configured to perform separable convolutions;
• a number of layers in the first neural network being smaller than a number of layers in the second neural network,
• the first neural network being configured to process an image at a first resolution and the second neural network being configured to process the same image at a lower resolution,
• a feature map of the first and second neural networks being combined by addition at a single stage;
• the training method comprising:
• providing training data, the training data comprising images and semantic segmented information concerning said images;
• training said model using said images as input and the semantic segmented information as output, wherein two stages are trained together.

An image processing system for segmenting an image, the system comprising:

• an interface and a processor,
• said interface having an image input and being adapted to receive a first image, said processor being adapted to;
• produce a second image from said first image, wherein said second image is a lower resolution representation of said first image;
• process said first image with a first processing stage to produce a first feature map;
• process said second image with a second processing stage to produce a second feature map;
• and
• combine the first feature map with the second feature map to produce a semantic segmented image;
• wherein the first processing stage comprises a first neural network comprising at least one separable convolution module configured to perform separable convolution and said second processing stage comprises a second neural network comprising at least one separable convolution module configured to perform separable convolution;
• a number of layers in the first neural network being smaller than a number of layers in the second neural network.