Abstract: A depth image generation method, apparatus, and storage medium and electronic device. The method includes: acquiring a plurality of target images; performing multi-stage convolution processing on the plurality of target images through a plurality of convolutional layers in a convolution model to obtain feature map sets respectively outputted by the plurality of convolutional layers; performing view aggregation on a plurality of feature maps in each feature map set respectively to obtain an aggregated feature corresponding to each feature map set; and performing fusion processing on the plurality of obtained aggregated features to obtain a depth image. The plurality of acquired target images are obtained by photographing the target object from different views respectively, so that the plurality of obtained target images include information from different angles, which enriches information content of the acquired target images.

Abstract: Embodiments of this application disclose a method and an apparatus for reconstructing a three-dimensional model of a human body, and a storage medium. The method includes obtaining a two-dimensional image of a human body part to be reconstructed; mapping the two-dimensional image to a voxel space, to obtain a voxelized result of the two-dimensional image; obtaining three-dimensional morphable model parameters corresponding to the two-dimensional image based on calculating the voxelized result using a preset three-dimensional parameter regression network; and reconstructing a three-dimensional model of the human body part based on the three-dimensional morphable model parameters.

Abstract: Embodiments of this application disclose a method and an apparatus for reconstructing a three-dimensional model of a human body, and a storage medium. The method includes obtaining a two-dimensional image of a human body part to be reconstructed; mapping the two-dimensional image to a voxel space, to obtain a voxelized result of the two-dimensional image; obtaining three-dimensional morphable model parameters corresponding to the two-dimensional image based on calculating the voxelized result using a preset three-dimensional parameter regression network; and reconstructing a three-dimensional model of the human body part based on the three-dimensional morphable model parameters.