Optimizer based prunner for neural networks

    公开(公告)号:US12254412B2

    公开(公告)日:2025-03-18

    申请号:US18096338

    申请日:2023-01-12

    Applicant: Snap Inc.

    Abstract: A neural network pruning system can sparsely prune neural network models using an optimizer based approach that is agnostic to the model architecture being pruned. The neural network pruning system can prune by operating on the parameter vector of the full model and the gradient vector of the loss function with respect to the model parameters. The neural network pruning system can iteratively update parameters based on the gradients, while zeroing out as many parameters as possible based a preconfigured penalty.

    Light estimation method for three-dimensional (3D) rendered objects

    公开(公告)号:US12299810B2

    公开(公告)日:2025-05-13

    申请号:US17846918

    申请日:2022-06-22

    Applicant: Snap Inc.

    Abstract: A method for applying lighting conditions to a virtual object in an augmented reality (AR) device is described. In one aspect, the method includes generating, using a camera of a mobile device, an image, accessing a virtual object corresponding to an object in the image, identifying lighting parameters of the virtual object based on a machine learning model that is pre-trained with a paired dataset, the paired dataset includes synthetic source data and synthetic target data, the synthetic source data includes environment maps and 3D scans of items depicted in the environment map, the synthetic target data includes a synthetic sphere image rendered in the same environment map, applying the lighting parameters to the virtual object, and displaying, in a display of the mobile device, the shaded virtual object as a layer to the image.

Patent Agency Ranking