Patent ID: 11922707
Assignee: BIGO TECHNOLOGY PTE. LTD.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A method for training a face detection model, comprising: acquiring a training face image;
performing three-dimensional reconstruction on the training face image based on a preset three-dimensional face model, and acquiring a training three-dimensional face model;
generating a training UV coordinate map comprising three-dimensional coordinates of the training three-dimensional face model based on the training three-dimensional face model, wherein U is a horizontal coordinate and V is a vertical coordinate; and
extracting the training face image;
inputting the training face image into a semantic segmentation network to extract a predicted UV coordinate map;
calculating a loss rate of the predicted UV coordinate map by using a preset loss function and the training UV coordinate map;
calculating a gradient by using the loss rate;
judging whether the gradient satisfies a preset iteration condition;
if yes, determining the semantic segmentation network as a face detection model;
performing gradient descent on a network parameter of the semantic segmentation network by using the gradient and a preset learning rate;
if no, returning to the step of extracting the training face image;
wherein performing the three-dimensional reconstruction on the training face image based on the preset three-dimensional face model, and acquiring the training three-dimensional face model comprises:
selecting M three-dimensional face models;
performing principal component analysis on the M three-dimensional face models, and acquiring a principal component matrix and an eigenvalue matrix; and
performing three-dimensional reconstruction on each training face image by using the principal component matrix and the eigenvalue matrix, and acquiring the training three-dimensional face model.