Efficient neural network encoding ford 3d color lookup tables

An apparatus for encoding color lookup tables (LUTs), comprising:

• a memory storing instructions;
• and
• one or more processors communicatively coupled to the memory;
• wherein the one or more processors are configured to execute the instructions to:
• determine a first identifier corresponding to a first LUT of a plurality of LUTs, each LUT of the plurality of LUTs comprising mappings from input color values to output color values;
• provide, to a trained machine learning model, the first identifier and an input lattice, the trained machine learning model having been jointly trained on the plurality of LUTs and identification information corresponding to each LUT in the plurality of LUTs;
• obtain, from the trained machine learning model, an output lattice corresponding to the first LUT;
• and
• perform color manipulation on at least one input image using the output lattice.

A non-transitory computer-readable storage medium storing computer-executable instructions for encoding color lookup tables (LUTs) by an apparatus that, when executed by at least one processor of the apparatus, cause the apparatus to:

• determine a first identifier corresponding to a first LUT of a plurality of LUTs, each LUT of the plurality of LUTs comprising mappings from input color values to output color values;
• provide, to a trained machine learning model, the first identifier and an input lattice, the trained machine learning model having been jointly trained on the plurality of LUTs and identification information corresponding to each LUT in the plurality of LUTs;
• obtain, from the trained machine learning model, an output lattice corresponding to the first LUT;
• and
• perform color manipulation on at least one input image using the output lattice.