Abstract: A method for determining a texture for a target expression comprises: determining feature graphs for the target expression and each of P training poses; determining blending weights tv based on: an approximation model trained using the training poses and a similarity metric ?v,t representing a similarity of the target feature graph at a vertex v to each of the training feature graphs; for each pixel in a plurality of 2D pixels: determining one or more vertices that correspond with the pixel based on 2D coordinates of the pixel and a mapping of the vertices to 2D; and determining per-pixel blending weights rn for the pixel based on the blending weights tv for the corresponding vertices. The method also comprises, for each high-resolution pixel in a 2D rendering of the target facial expression, interpolating 2D textures of the training facial poses based on the per-pixel blending weights rn to thereby provide the target texture.

Abstract: Generating a 3D representation of a subject includes obtaining an image of a physical subject. Front depth data is obtained for a front portion of the physical subject. Back depth data is obtained for the physical subject based on the image and the front depth data. A set of joint locations is determined for the physical subject from the image, the front depth data, and the back depth data.

Abstract: Systems and methods for animating from audio in accordance with embodiments of the invention are illustrated. One embodiment includes a method for generating animation from audio. The method includes steps for receiving input audio data, generating an embedding for the input audio data, and generating several predictions for several tasks from the generated embedding. The several predictions includes at least one of blendshape weights, event detection, and/or voice activity detection. The method includes steps for generating a final prediction from the several predictions, where the final prediction includes a set of blendshape weights, and generating an output based on the generated final prediction.

Abstract: Systems and methods for animating from audio in accordance with embodiments of the invention are illustrated. One embodiment includes a method for generating animation from audio. The method includes steps for receiving input audio data, generating an embedding for the input audio data, and generating several predictions for several tasks from the generated embedding. The several predictions includes at least one of blendshape weights, event detection, and/or voice activity detection. The method includes steps for generating a final prediction from the several predictions, where the final prediction includes a set of blendshape weights, and generating an output based on the generated final prediction.