| CPC G06T 15/005 (2013.01) [G06T 7/97 (2017.01); G06T 2207/20084 (2013.01)] | 20 Claims |
|
1. A processor comprising: one or more circuits to:
generate, using a text-to-3D model, one or more three-dimensional (3D) objects from a training text input;
sample, via stratified sampling over respective ranges, one or more stratified training data parameters that includes one or more camera orientation parameters, and at least one of a timestep length or a noise component;
render one or more images at least partially depicting the one or more 3D objects using the one or more camera orientation parameters;
generate, using a text-to-image model, through a plurality of diffusion steps each having the timestep length, a predicted noise component based on the training text input and at least one rendered image added with the noise component;
compute a gradient based on the predicted noise and stratified training data parameters; and
generate, from a text input, one or more 3D images using one or more neural networks trained based, at least in part, on the gradient computed with the stratified sampled training data parameters.
|