Beijing Baidu Netcom Science and Technology Co., Ltd.

Baidu Online Network Technology (Beijing) Co., Ltd.

Beijing Baidu Netcom Science Technology Co., Ltd

Baidu Online Network Technology Co., Ltd.

Zhe Peng

Yuqiang Liu

Guanbo Bao

Tao Sun

Lei Jia

Wenfu Wang

Xiang Xu

Huan Ye

Minqiang Chang

Fanyu Geng

A method of generating a 3D video, a method of training a neural network model, an electronic device, and a storage medium, which relate to a field of image processing, and in particular to technical fields of computer vision, augmented/virtual reality and deep learning. The method includes: determining, based on an input speech feature, a principal component analysis (PCA) coefficient by using a first network, wherein the PCA coefficient is used to generate the 3D video; correcting the PCA coefficient by using a second network; generating a lip movement information based on the corrected PCA coefficient and a PCA parameter for a neural network model, wherein the neural network model includes the first network and the second network; and applying the lip movement information to a pre-constructed 3D basic avatar model to obtain a 3D video with a lip movement effect.

Method of generating 3D video, method of training model, electronic device, and storage medium

The disclosure provides a method for generating a three-dimensional virtual image. The method includes: obtaining a face image to be processed and a three-dimensional reference model; obtaining a three-dimensional face model, face attribute information and face image information by inputting the face image to be processed into a trained neural network; obtaining a three-dimensional image model by performing a deformation process on the three-dimensional reference model based on the three-dimensional face model; and obtaining a target virtual image by adjusting the three-dimensional image model based on the face attribute information and the face image information.

Method and apparatus for generating three-dimensional virtual image, and storage medium

A method and apparatus for predicting a mouth-shape feature, and an electronic device are provided. A specific implementation of the method comprises: recognizing a phonetic posterior gram (PPG) of a phonetic feature; and performing a prediction on the PPG by using a neural network model, to predict a mouth-shape feature of the phonetic feature, the neural network model being obtained by training with training samples and an input thereof including a PPG and an output thereof including a mouth-shape feature, and the training samples including a PPG training sample and a mouth-shape feature training sample.

Method and apparatus for predicting mouth-shape feature, and electronic device

A method, an apparatus, a device and a computer-readable storage medium for recognizing aerial handwriting are provided. The method may include detecting a palm region of a user in a two-dimensional grayscale image; detecting a fingertip in the two-dimensional gray-scale image based on the palm area; determining a spatial trajectory of the fingertip based on a set of two-dimensional gray-scale images, the set of two-dimensional gray-scale images including the two-dimensional gray-scale image; and recognizing handwritten content of the user based on the spatial trajectory. A two-dimensional gray-scale image is used to recognize and track the spatial trajectory of the fingertip, which may speed up aerial handwriting recognition, and has low processing performance requirements for the device, while also ensuring high accuracy.

Method, apparatus, device and computer readable storage medium for recognizing aerial handwriting

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Beijing, China

Zhe Peng