Utilizing interactive deep learning to select objects in digital visual media

A system comprising:

• a memory component;
• and
• one or more processing devices coupled to the memory component, the one or more processing devices to perform operations comprising:
• generating, utilizing a neural network, predicted pixels corresponding to training objects utilizing digital training images portraying the training objects and training indicators comprising pixels and indications of how the pixels correspond to the training objects by:
• generating, for a digital training image of the digital training images, a training distance map by determining distances between pixels in the digital training image and a training indicator corresponding to the digital training image;
• and
• generating the predicted pixels from the training distance map utilizing the neural network;
• comparing the predicted pixels corresponding to the training objects with training ground truth masks;
• and
• training the neural network by comparing the predicted pixels corresponding to the training objects with the training ground truth masks.

A non-transitory computer-readable medium storing executable instructions which, when executed by a processing device, cause the processing device to perform operations comprising:

• generating, utilizing a neural network, predicted pixels corresponding to training objects utilizing digital training images portraying the training objects and training indicators comprising pixels and indications of how the pixels correspond to the training objects by:
• generating, for a digital training image of the digital training images, a training distance map by determining distances between pixels in the digital training image and a training indicator corresponding to the digital training image;
• and
• generating the predicted pixels from the training distance map utilizing the neural network;
• comparing the predicted pixels corresponding to the training objects with training ground truth masks;
• and
• training the neural network by comparing the predicted pixels corresponding to the training objects with the training ground truth masks.