Computing method and apparatus with image generation

A non-transitory computer-readable storage medium storing instructions that, when executed by a processor, cause the processor to execute a method of generating an image, the method comprising:

• receiving input data comprising conditional information and image information, wherein the image information includes geometric information;
• receiving depth information corresponding to the conditional information;
• extracting feature information from the depth information;
• generating a synthesized image based on the conditional information by applying the input data and the feature information to an image generation neural network, the image generation neural network is configured to:
• maintain the geometric information of the image information;
• and
• transform, based on the conditional information, first remaining image information of the image information to second remaining image information;
• and
• outputting the synthesized image.

A computing apparatus, the apparatus comprising:

• a communication circuit configured to:
• receive input data including conditional information and image information, wherein the image information includes geometric information;
• and
• receive depth information corresponding to the conditional information;
• a processor configured to:
• extract feature information from the depth information;
• and
• generate a synthesized image based on the conditional information by applying the input data and the feature information to an image generation neural network, wherein the image generation neural network is configured to:
• maintain the geometric information of the image information;
• and
• transform, based on the conditional information, first remaining image information of the image information to second remaining image information;
• and
• an output circuit configured to output the synthesized image.

A processor-implemented method, the method comprising:

• receiving training data comprising conditional information and image information;
• receiving depth information corresponding to the conditional information;
• generating a first synthesized image corresponding to the conditional information by an image generation neural network based on the image information;
• transforming the conditional information based on the depth information;
• generating a second synthesized image corresponding to the transformed conditional information by the image generation neural network based on the image information;
• and
• training the image generation neural network by comparing the first synthesized image and the second synthesized image based on a transformation relationship of the conditional information.

A processor-implemented method, the method comprising:

• receiving training data comprising image information, conditional information, and depth information corresponding to the conditional information;
• extracting depth feature information from the depth information;
• generating a first synthesized image corresponding to the depth feature information and the conditional information by the image generation neural network based on the image information;
• transforming the conditional information and the depth feature information based on the depth information;
• generating a second synthesized image corresponding to the transformed conditional information and the transformed depth feature information by the image generation neural network based on the image information;
• and
• training the image generation neural network by comparing the first synthesized image and the second synthesized image based on a transformation relationship of the conditional information and the depth information.