Methods, storage media, and systems for iteratively texturing a three-dimensional model with consistent predictions

A method implemented by a system of one or more processors, the method comprising:

• accessing a three-dimensional model associated with a building, the three-dimensional model being associated with geometry which is included in a scene;
• generating, via one or more machine learning models, a first viewpoint of the scene from a first viewpoint angle, the first viewpoint including textures applied to the three-dimensional model from the first viewpoint angle and additional image content generated based on at least one parameter;
• extracting, via one or more machine learning models, updated geometry for inclusion in the scene, wherein the updated geometry includes geometry associated with the additional image content at the first viewpoint angle;
• and
• generating, via one or more machine learning models, a second viewpoint of the scene from a second viewpoint angle, where generating the second viewpoint is based on the updated geometry.

A method implemented by a system of one or more processors, wherein the system generates a user interface for presentation via a user device, and wherein the user interface:

• requests a textual or visual prompt indicative of features to be included in a three-dimensional scene, and receives input of a three-dimensional model associated with a building;
• triggers generation of viewpoints of the scene from a plurality of viewpoint angles, wherein the viewpoints represent image rendering of the scene, and wherein the three-dimensional model is associated with geometry, wherein the system is configured to:
• generate, via one or more machine learning models, individual viewpoints from individual viewpoint angles,
• wherein the machine learning models are input textures applied to geometry which form the scene from an individual viewpoint angle, wherein the geometry is determined using the three-dimensional model and geometry extracted from additional image content generated using the machine learning models for one or more prior viewpoint angles;
• and
• presents at least one of the viewpoints.

A method implemented by a system of one or more processors, the method comprising:

• accessing a three-dimensional model associated with a building, the three-dimensional model being associated with geometry and semantic labels;
• generating, via one or more machine learning models, textures to be applied to the three-dimensional model, wherein generating textures is based on at least one parameter, and wherein the parameter is analyzed to identify particular semantic labels which are input into the one or more machine learning models;
• in response to a viewpoint change, extracting, via one or more machine learning models, updated geometry based on the generated textures and the geometry associated with the three-dimensional model, wherein the updated geometry includes additional geometry reflective of a portion of the textures associated with the at least one parameter;
• and
• generating, via one or more machine learning models, textures to be applied to the updated geometry.

A method implemented by a system of one or more processors, the method comprising:

• accessing a three-dimensional model which is associated with a depth map;
• generating a texture for the three-dimensional model via one or more machine learning models based on a prompt indicative of the texture, wherein the one or more machine learning models generate texture portions which form the texture based on a plurality of views of the three-dimensional model, and wherein generating the texture portions comprises iteratively:
• generating an individual texture portion via the one or more machine learning models based on input comprising the prompt, an individual portion of the depth map which is associated with an individual view of the three-dimensional model, an individual rendering of the three-dimensional model at the individual view which includes a previously applied texture portion,
• wherein the individual texture portion is applied to the three-dimensional model at least a subset of positions for which a texture portion has not been applied,
• wherein the three-dimensional model is configured for presentation.