Abstract: A method of generating a stylized 3D avatar is provided. The method includes receiving an input image of a user, generating, using a generative adversarial network (GAN) generator, a stylized image, based on the input image, and providing the stylized image to a first model to generate a first plurality of parameters. The first plurality of parameters include a discrete parameter and a continuous parameter. The method further includes providing the stylized image and the first plurality of parameters to a second model that is trained to generate an avatar image, receiving, from the second model, the avatar image, comparing the stylized image to the avatar image, based on a loss function, to determine an error, updating the first model to generate a second plurality of parameters that correspond to the first plurality of parameters, based on the error, and providing the second plurality of parameters as an output.

Abstract: A method of generating a style image is described. The method includes receiving an input image of a subject. The method further includes encoding the input image using a first encoder of a generative adversarial network (GAN) to obtain a first latent code. The method further includes decoding the first latent code using a first decoder of the GAN to obtain a normalized style image of the subject, wherein the GAN is trained using a loss function according to semantic regions of the input image and the normalized style image.

Abstract: Systems and methods for rendering a translucent object are provided. In one aspect, the system includes a processor coupled to a storage medium that stores instructions, which, upon execution by the processor, cause the processor to receive at least one mesh representing at least one translucent object. For each pixel to be rendered, the processor performs a rasterization-based differentiable rendering of the pixel to be rendered using the at least one mesh and determines a plurality of values for the pixel to be rendered based on the rasterization-based differentiable rendering. The rasterization-based differentiable rendering can include performing a probabilistic rasterization process along with aggregation techniques to compute the plurality of values for the pixel to be rendered. The plurality of values includes a set of color channel values and an opacity channel value. Once values are determined for all pixels, an image can be rendered.

Abstract: Disclosed herein are devices, systems, and methods that provide improved tunneling magnetoresistance (TMR) through the use of innovative device structures and heterostructure layers therein. Particularly, two or more magnetic layers form a heterostructure core of the switching device, with control of current passing through the heterostructure determined by an applied magnetic field that modifies the magnetization of the heterostructure from a ground magnetic state that is layered antiferromagnetic.

Abstract: Disclosed herein are devices, systems, and methods that provide improved tunneling magnetoresistance (TMR) through the use of innovative device structures and heterostructure layers therein. Particularly, two or more magnetic layers form a heterostructure core of the switching device, with control of current passing through the heterostructure determined by an applied magnetic field that modifies the magnetization of the heterostructure from a ground magnetic state that is layered antiferromagnetic.