Abstract: The present disclosure relates to a method for music generation, an electronic device and a storage medium. The method includes: determining first tag information of a first object by recognizing the first object; determining target background music based on the first tag information, in which the target background music includes lyrics template information which includes information about a number of words per sentence in lyrics suitable for the target background music; determining second tag information by extracting a tag of a second object; and displaying first lyrics on a music display page according to the second tag information and the lyrics template information, and playing the target background music, in which a form of the target background music includes rap.

Abstract: The present disclosure relates to a method and an apparatus for training a 6D pose estimation network based on deep learning iterative matching. The method includes: obtaining a rendered image and a first segmentation mask of a target object by using a 3D model and an initial 6D pose estimation of the target object; inputting the rendered image, the first segmentation mask, an observed image of the target object, and a second segmentation mask of the target object in the observed image into a deep convolutional neural network to obtain a 6D pose estimation, a third segmentation mask and an optical flow; and performing said obtaining and said inputting again by updating the initial 6D pose estimation using the obtained relative 6D pose estimation and replacing the second segmentation mask with the third segmentation mask, to iteratively train the deep convolutional neural network.

Abstract: The present disclosure relates to a method and an apparatus for training a 6D pose estimation network based on deep learning iterative matching. The method includes: obtaining a rendered image and a first segmentation mask of a target object by using a 3D model and an initial 6D pose estimation of the target object; inputting the rendered image, the first segmentation mask, an observed image of the target object, and a second segmentation mask of the target object in the observed image into a deep convolutional neural network to obtain a 6D pose estimation, a third segmentation mask and an optical flow; and performing said obtaining and said inputting again by updating the initial 6D pose estimation using the obtained relative 6D pose estimation and replacing the second segmentation mask with the third segmentation mask, to iteratively train the deep convolutional neural network.

Abstract: Disclosed is a pipe expanding punch for a drill, which is configured to expand a pipe by hitting the pipe by an anchor drill or a rechargeable drill. The pipe expanding punch includes: an expanding mandrel provided with at least one portion (hereinafter referred to as “an expanding part”) having an outer diameter larger than an inner diameter of a pipe to be expanded; and a holder formed integrally with the expanding mandrel and fixedly coupled to a drill such that the pipe is expanded using the drill, wherein the outer diameter of an introduction part of an end portion of the expanding mandrel is smaller than the inner diameter of the pipe, a first tapered step is provided between the introduction part and the expanding part, and at least one polished flat surface is formed by polishing the first tapered step.