Abstract: The present disclosure describes techniques for implementing dialog-based image editing. Text indicating a task of editing an image is received. A list of objects and attributes associated with each of the objects is generated based on the text and the image. The objects are comprised in the image. Operations to be performed on each of the objects are determined. An order of performing the operations on an object-by-object basis are determined. A plan of implementing the task is generated based on the text and the order of performing the operations. The plan comprises information indicating a set of algorithm tools selected for the task. Executable code is generated based at least in part on the plan. The code is executed to generate an edited image.

Abstract: A computer-implemented method for transforming a neural radiance field model is described. A plurality of inputs are provided to a neural radiance field (NeRF) model that represents a 3-dimensional space having a subject, wherein each input of the plurality of inputs includes a location and a view direction and corresponds to respective colors of voxels that represent the 3-dimensional space. A spectral analysis is performed on a plurality of outputs of the NeRF model based on the plurality of inputs, wherein the plurality of outputs include the respective colors of the voxels. Frequency components of the spectral analysis that represent colors for at least some of the voxels are extracted. A sparse volume data structure that represents the 3-dimensional space and the respective colors for the at least some of the voxels is generated.

Abstract: Examples of memory-efficient volume data structures for novel view rendering are provided. In one aspect, a computing device for rendering a model volume data structure is provided. The computing device comprises a processor coupled to a storage medium that stores instructions, which, upon execution by the processor, cause the processor to store the model volume data structure, wherein the model volume data structure comprises a B+ tree graph, determine a camera view in which to render the model volume data structure, determine a plurality of rays in three-dimensional space based on the camera view, for each ray in the plurality of rays, perform a ray-marching process using the model volume data structure to determine a plurality of color features, and render the model volume data structure using the pluralities of color features.

Abstract: A graphics-specific search engine receives a search input from a user account for a media platform, determines a search query parsed from the input, and searches a graphics-specific database for existing images that correspond to the search query. An image generator generates new images that correspond to the search query when the search result does not exceed a predetermined number. A graphics display engine sends a plurality of the images to an instance of an account for a media platform.

Abstract: A computer-implemented method for transforming a neural radiance field model is described. A plurality of inputs are provided to a neural radiance field (NeRF) model that represents a 3-dimensional space having a subject, wherein each input of the plurality of inputs includes a location and a view direction and corresponds to respective colors of voxels that represent the 3-dimensional space. A spectral analysis is performed on a plurality of outputs of the NeRF model based on the plurality of inputs, wherein the plurality of outputs include the respective colors of the voxels. Frequency components of the spectral analysis that represent colors for at least some of the voxels are extracted. A sparse volume data structure that represents the 3-dimensional space and the respective colors for the at least some of the voxels is generated.