Techniques for interactive image segmentation networks

At least one non-transitory computer-readable medium comprising instructions that cause one or more first processor circuits to:

• conduct a neural architecture search to select respective values for hyperparameters of a machine learning (ML) model, the ML model associated with a neural architecture having one or more encoders, one or more decoders, and one or more skip connections between the one or more encoders and the one or more decoders, the hyperparameters indicative of a first number of the one or more encoders and the one or more decoders to be included in the neural architecture, a second number of convolutional layers within respective ones of the one or more decoders, and a size of dilation in the respective ones of the one or more decoders;
• and
• cause interface circuitry to deploy the ML model with the respective values for the hyperparameters, the ML model to cause one or more second processor circuits to:
• based on a first encoding frame with a first resolution, generate, with a first encoder, first output data including a second encoding frame with a second resolution;
• and
• generate, with a first decoder, second output data including a first decoding frame with the first resolution based on a second decoding frame with the second resolution and a context frame with the second resolution.

An apparatus, comprising:

• means for optimizing respective values for hyperparameters of a machine learning (ML) model, the ML model associated with a neural architecture having one or more encoders, one or more decoders, and one or more skip connections between the one or more encoders and the one or more decoders, the hyperparameters indicative of a first number of the one or more encoders and the one or more decoders to be included in the neural architecture, a second number of convolutional layers within respective ones of the one or more decoders, and a size of dilation in the respective ones of the one or more decoders;
• and
• means for deploying the ML model with the respective values for the hyperparameters, the ML model to cause:
• means for generating, with a first encoder, first output data based on a first encoding frame with a first resolution, the first output data including a second encoding frame with a second resolution;
• and
• means for generating, with a first decoder, second output data including a first decoding frame with the first resolution based on a second decoding frame with the second resolution and a context frame with the second resolution.