Neural animation layering for synthesizing martial arts movements

A system comprising one or more processors and non-transitory computer storage media storing instructions that when executed by the one or more processors, cause the one or more processors to perform operations comprising:

• receiving a current frame of a virtual character within a virtual environment of an instance of a video game, wherein the current frame includes current pose data for the virtual character;
• identifying a plurality of possible behaviors for the virtual character for the next frame based on the current pose data in the current frame, wherein the next frame is a subsequent frame to the current frame;
• receiving, from a user of the video game, an input to perform at least a first and second behavior of the plurality of possible behaviors;
• determining a plurality of pose data for the first and second behavior;
• performing layering of the plurality of pose data corresponding to the first and second behavior on the current pose data to generate layered data;
• applying the layered data to a gating network to generate weights;
• and
• applying the weights to a pose predictor network configured to generate next pose data for the next frame.

A non-transitory computer storage media storing instructions that when executed by a system of one or more processors, cause the one or more processors to perform operations comprising:

• receiving a current frame of a virtual character within a virtual environment of an instance of a video game, wherein the current frame includes current pose data for the virtual character;
• identifying a plurality of possible behaviors for the virtual character for the next frame based on the current pose data in the current frame, wherein the next frame is a subsequent frame to the current frame;
• receiving, from a user of the video game, an input to perform at least a first and second behavior of the plurality of possible behaviors;
• determining a plurality of pose data for the first and second behavior;
• performing layering of the plurality of pose data corresponding to the first and second behavior on the current pose data to generate layered data;
• applying the layered data to a gating network to generate weights;
• and
• applying the weights to a pose predictor network configured to generate next pose data for the next frame.