Automated semantic inference of visual features and scenes

A processing device to perform scene recognition, comprising:

• interface circuitry to receive visual data captured by one or more sensors;
• and
• processing circuitry to:
• detect a first set of objects in the visual data based on one or more first machine learning models, wherein the one or more first machine learning models are trained to detect the first set of objects;
• determine, based on detecting the first set of objects, that the visual data is expected to contain a second object, wherein the second object is related to at least a subset of the first set of objects;
• detect the second object in the visual data based on a second machine learning model, wherein the second machine learning model is trained to detect the second object;
• and
• recognize a scene captured in the visual data, wherein the scene is recognized based on detecting the first set of objects and the second object in the visual data.

At least one non-transitory machine accessible storage medium having instructions stored thereon, wherein the instructions, when executed on processing circuitry, cause the processing circuitry to:

• receive, via interface circuitry, visual data captured by one or more sensors;
• detect a first set of objects in the visual data based on one or more first machine learning models, wherein the one or more first machine learning models are trained to detect the first set of objects;
• determine, based on detecting the first set of objects, that the visual data is expected to contain a second object, wherein the second object is related to at least a subset of the first set of objects;
• detect the second object in the visual data based on a second machine learning model, wherein the second machine learning model is trained to detect the second object;
• and
• recognize a scene captured in the visual data, wherein the scene is recognized based on detecting the first set of objects and the second object in the visual data.

A method of performing scene recognition, comprising:

• receiving, via interface circuitry, visual data captured by one or more sensors;
• detecting a first set of objects in the visual data based on one or more first machine learning models, wherein the one or more first machine learning models are trained to detect the first set of objects;
• determining, based on detecting the first set of objects, that the visual data is expected to contain a second object, wherein the second object is related to at least a subset of the first set of objects;
• detecting the second object in the visual data based on a second machine learning model, wherein the second machine learning model is trained to detect the second object;
• and
• recognizing a scene captured in the visual data, wherein the scene is recognized based on detecting the first set of objects and the second object in the visual data.

A system for performing scene recognition, comprising:

• a camera to capture visual data of an environment;
• and
• processing circuitry to:
• detect a first set of objects in the visual data based on one or more first machine learning models, wherein the one or more first machine learning models are trained to detect the first set of objects;
• determine, based on detecting the first set of objects, that the visual data is expected to contain a second object, wherein the second object is related to at least a subset of the first set of objects;
• detect the second object in the visual data based on a second machine learning model, wherein the second machine learning model is trained to detect the second object;
• and
• recognize a scene captured in the visual data, wherein the scene is recognized based on detecting the first set of objects and the second object in the visual data.