| CPC G06T 7/194 (2017.01) [G06T 17/00 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01)] | 20 Claims |

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1. A computer-implemented method, the method comprising:
obtaining, by a computing system comprising one or more processors, a foreground neural radiance field model, wherein the foreground neural radiance field model was trained to render one or more objects from a particular object category based on a loss function that evaluates differences between outputs of the foreground neural radiance field model and a plurality of training images, wherein the plurality of training images are descriptive of the one or more objects in the particular object category;
obtaining, by the computing system, an input position, an input view direction, and an object embedding, wherein the object embedding is associated with a particular object in the particular object category;
processing, by the computing system, the input position, the input view direction, and the object embedding with the foreground neural radiance field model to generate a foreground output, wherein the foreground output comprises a foreground color output and a foreground density output;
processing, by the computing system, the input position and the input view direction with a background neural radiance field model to generate a background output, wherein the background output comprises a background color output and a background density output; and
generating, by the computing system, a rendering comprising the particular object in an environment based at least in part on the foreground output and the background output.
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